LimaCharlie MCP

by geoffbelknap

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation4/5
Tools are generally distinct with clear descriptions, but the sheer volume (297) and the preview/confirm pattern create some ambiguity. For example, many preview tools exist for similar actions (e.g., add/remove case entities), which could confuse an agent when selecting the right one.
Naming Consistency5/5
All tools follow a strict 'lc_verb_noun' pattern in snake_case, making them highly predictable. The naming is uniform across all 297 tools, with clear prefixes and consistent verb choices (get, list, preview, etc.).
Tool Count1/5
297 tools is far beyond what is reasonable for a single server. Even for a comprehensive API, this overwhelms both developers and AI agents. Typical well-scoped servers have 3-15 tools. The count suggests poor scoping and lack of consolidation.
Completeness4/5
The tool set covers a vast range of operations across many domains (auth, sensors, detections, cases, AI, Hive records, etc.), including CRUD-like operations via preview tools. Minor gaps exist, such as no direct non-preview write tools (all writes require preview+confirm), but the coverage is otherwise thorough.
Average 2.6/5 across 288 of 297 tools scored. Lowest: 1.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 58 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The word 'Preview' suggests a non-destructive simulation, but the description does not explicitly confirm no side effects, auth requirements, or output format. With no annotations, the description fails to provide adequate transparency about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is under-specified. It lacks critical details, making it more of a placeholder than a helpful guide.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, no annotations, and many sibling preview tools, the description is far from complete. It does not explain what 'component' or 'oid' refer to, how token_ttl_seconds is used, or what the preview result looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameter descriptions are provided in the input schema (0% coverage), and the description does not mention or explain any of the three parameters (oid, component, token_ttl_seconds). This leaves the agent with no semantic meaning beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview dismissing one organization component error' gives a basic idea of the action but uses vague terms like 'component' and doesn't specify what the preview entails. It barely distinguishes from other preview tools, which all start with 'lc_preview_', but it does indicate it's a preview operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling preview tools for different actions (add, remove, set, etc.), the lack of context leaves the agent without decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only says 'preview', implying a read-only or dry-run operation, but doesn't confirm safety, side effects, or required permissions. Lack of detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (1 sentence), but it sacrifices informativeness. Conciseness is positive only if the message is clear; here it's under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, high parameter count (6), and no annotations, the description is severely incomplete. It fails to explain the preview's purpose, behavior, or return value, making it nearly useless for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds no explanation for any of the 6 parameters (oid, data, action, impersonate, extension_name, token_ttl_seconds). The agent cannot infer parameter roles or constraints from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview a generic extension request' is a tautology of the tool name, adding no specific detail about what 'preview' entails or what an 'extension request' is. It doesn't differentiate from other lc_preview_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling lc_preview_* tools, the description should specify the context, but it provides none.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description uses 'Preview' to imply a non-destructive operation but does not explicitly state that no changes are made, nor does it mention prerequisites, return value, or potential side effects. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence description is brief but at the expense of clarity. It under-specifies the tool, omitting essential details that could be added in a few more sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and 3 parameters with no descriptions, the tool definition is severely incomplete. An agent cannot reliably determine how to invoke or interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 3 parameters with 0% description coverage. The tool description does not explain what 'oid', 'extension_name', or 'token_ttl_seconds' mean, leaving the agent without guidance on how to fill them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview subscribing an org to an extension' is essentially a rephrasing of the tool name and lacks specificity about what 'preview' entails (e.g., validation, cost estimation, simulation). It does not distinguish itself from a potential actual subscribe tool if one existed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_preview_unsubscribe_extension or lc_list_extension_subscriptions. The description gives no context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as read-only nature, destructive potential, or authentication requirements. The description carries the full burden but fails to provide any transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one phrase) but sacrifices necessary detail. While brevity is valued, it omits critical information, making it under-specified rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and no parameter descriptions, the description is grossly insufficient. The agent lacks essential context to understand what the tool returns or how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the required 'oid' parameter. The agent cannot determine if 'oid' refers to an organization ID, case ID, or something else, making correct invocation impossible.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it retrieves 'Cases configuration' for an org, which is a specific resource distinct from sibling tools like 'get_case' or 'get_org_info'. However, it does not clarify what 'Cases configuration' includes, making the purpose somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks context about prerequisites, scenarios, or when not to use it, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure, but it does not mention side effects, auth needs, rate limits, or what 'enrichment' means. It is insufficient for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is vague and does not front-load critical information. The word 'enrichment-oriented' adds confusion rather than clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters with no descriptions, no output schema, and no annotations, the description is severely incomplete. An agent cannot rely on this definition to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about the parameters (oid, obj_type, obj_name, info, limit, wildcards, case_sensitive). The agent cannot understand how to use these parameters from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Lookup one object through Insight with enrichment-oriented naming', which gives a general verb+resource but the phrase 'enrichment-oriented naming' is ambiguous and does not clearly explain what the tool returns or how it differs from other get tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_get_detection or lc_get_sensor. The description does not specify any context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description gives no behavioral details—e.g., whether it actually performs or simulates the addition, permission requirements, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While very short, the description is underspecified rather than concise; it fails to earn its place by adding value beyond the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 6 parameters, absence of annotations and output schema, the description is grossly incomplete and insufficient for an agent to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and no parameter explanations in the description, the agent has no guidance on the meaning or usage of the 6 parameters beyond their names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview adding a note to a case' states the action (preview add) and resource (note to a case), but does not clarify what 'preview' entails or distinguish it from many sibling preview tools like lc_preview_add_case_artifact.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other preview tools or alternatives. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only says 'Preview creating an exfil watch rule,' which reveals no behavioral traits. Does it validate, simulate, or commit? Are there side effects? Does it require specific permissions? The agent is left completely in the dark.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
At 6 words, the description is extremely concise but sacrifices substance. It is front-loaded but fails to convey necessary information. No structure, such as bullet points or context, to help the agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 6 required, no output schema), the description is grossly incomplete. The agent has no idea what the preview returns, what parameters do, or what scenarios this tool is for. This is a critical gap for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides zero information about the 9 parameters, including critical ones like 'oid', 'event', 'value', 'operator', and 'path'. The agent cannot infer what values are expected or how they relate to an exfil watch rule.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Preview creating an exfil watch rule', indicating a specific verb and resource. However, it is too terse and does not differentiate this tool from other preview tools (e.g., lc_preview_create_exfil_event, lc_preview_create_case). The concept of 'preview' is not elaborated, leaving ambiguity about what the tool actually does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as lc_list_exfil_rules, lc_preview_delete_exfil_watch, or the actual create tool. Missing context on prerequisites, whether this is a dry run, or when a user would need this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description fails to disclose any behavioral traits such as side effects, whether the action is reversible, or what 'preview' entails (e.g., does it create a temporary state?). The description is insufficient for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence), but it sacrifices necessary detail. It is not appropriately sized for the tool's complexity and does not earn its place because it omits critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and no annotations, the description should provide more context. It fails to explain the purpose of 'preview', what the output looks like, or how the parameters relate to the action. The tool is left largely undefined.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the parameters (oid, name, token_ttl_seconds). The agent cannot infer what each parameter represents or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Preview deleting' and the resource 'a payload', which is clear. However, 'preview' is not explained, and it does not distinguish this tool from many other preview_delete_* siblings beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., actual delete tools or other preview_delete tools). No context on prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'preview toggling'. It doesn't explain if this is a safe read-only operation or a mutation, what side effects exist, or if authentication is needed. The word 'preview' hints at non-destructive behavior, but it's not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence), but it lacks necessary detail. It prioritizes brevity over completeness, resulting in under-specification rather than concise clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no annotations, and no output schema, the description is drastically incomplete. It fails to explain what 'preview' means, what the tool returns, how token_ttl_seconds is used, or how this differs from related tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate. However, it only mentions 'enabled metadata' without explaining any of the 4 parameters (oid, name, enabled, token_ttl_seconds). It adds no semantic meaning beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it's about toggling enabled metadata for an SOP Hive record, which aligns with the tool name. However, the term 'preview' is ambiguous—does it dry-run or actually toggle? The sibling tools like lc_preview_set_sop and lc_set_sop suggest a preview/cap, but the description doesn't clarify this distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this preview vs. the actual set operation (lc_set_sop) or other sibling preview tools. There's no mention of context, prerequisites, or exclusions, leaving the AI agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. The term 'Preview' hints at a dry-run or simulation nature, but no details are given about side effects, output format, or whether any state changes occur. This lack of transparency is a significant gap for a tool that could involve mutations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one short sentence), which aligns with conciseness, but it lacks structure. A single sentence fails to front-load key details or separate purpose from usage. While brevity is valued, it comes at the cost of completeness and clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no output schema, no annotations), the description is severely incomplete. It does not cover the meaning of 'preview', expected output, parameter roles, or any behavior beyond the vague action. This inadequacy hinders correct agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 7 parameters (oid, case_number, entity_type, entity_value, note, verdict, token_ttl_seconds). The agent receives no guidance on parameter meaning, valid values, or constraints, forcing reliance solely on parameter names which may be ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Preview adding') and resource ('entity/IOC to a case'), providing clear verb+resource identification. However, it does not differentiate from sibling tools like lc_preview_add_case_artifact or lc_preview_add_case_detection, which have similar structures. The purpose is clear but lacks specificity for distinguishing between similar preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not specify when to use this tool versus alternatives, nor does it mention any prerequisites or conditions. With many sibling preview tools, the absence of usage guidance leaves the agent without direction for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only implies a read operation but does not mention side effects, permissions, rate limits, or return structure. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but overly terse. It lacks structure and fails to provide necessary detail, making it under-specified rather than efficiently written.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters (3 required), no output schema, and no parameter descriptions. The minimal description does not compensate, leaving the agent without crucial context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should explain parameters but does not. It adds no meaning beyond the schema's property names. Users get no help on what oid, time_from, time_to, or group_by mean.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a verb ('Get') and a resource ('Cases report summary metrics'), but the term 'summary metrics' is vague and does not differentiate from siblings like lc_get_case or lc_get_cases_config. The purpose is partially clear but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lc_get_case, lc_list_cases). No context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The word 'Preview' hints at a non-destructive operation, but the description does not explicitly state that no actual key is created, what the side effects are, or what the return value represents. With no annotations, the description carries full burden and fails to disclose key behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (4 words). While it is concise, it is under-specified—it lacks essential details that should be present for a 5-parameter tool. Every sentence should earn its place, but this one fails to add value beyond the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, no output schema, no annotations), the description is severely incomplete. It does not explain the tool's behavior, output, or parameter usage, leaving the agent with insufficient information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about parameters (oid, description, tags, use_public_ca, token_ttl_seconds). The agent must infer their meanings from names alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Preview creating' and resource 'installation key', which is clear in general purpose. However, it does not differentiate from sibling preview tools (e.g., lc_preview_delete_installation_key) or explain what 'preview' specifically entails (simulation, validation, etc.). It is not a tautology but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like actual creation (if exists) or other preview tools. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry full burden. It does not disclose whether this tool is destructive, whether it actually pushes changes or just simulates, or any permissions required. The term 'preview' implies non-destructive, but it's not confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only one sentence, but it is under-specified and lacks structure. Conciseness should not come at the cost of clarity; here, it fails to convey necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 16 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain key concepts like 'org IaC configuration' or 'ext-infrastructure', and how the various sync parameters interact. The tool is likely complex, but the description is minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameter descriptions are empty. The description adds no meaning to any of the 16 parameters, including critical ones like 'config' (an object) and many boolean sync flags. The agent cannot understand what each parameter does from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview pushing org IaC configuration through ext-infrastructure' gives a general idea but is vague. It mentions 'preview' which suggests it's a dry-run, but it's not explicit. The name and sibling tools indicate it's one of many preview operations, but the description doesn't distinguish what this specific preview does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The sibling list includes many preview tools (e.g., lc_preview_set_config, lc_preview_create_org), but the description provides no context for differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must carry the burden. It calls the tool a 'preview' but does not clarify whether it actually sets the config or just simulates the change. No information on permissions, side effects, rate limits, or rollback. The behavior is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (4 words), but under-specification is not conciseness. It lacks essential detail while offering minimal information. A good concise description would pack more value per word.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is grossly incomplete. The agent has insufficient information to determine input requirements, expected behavior, or return value. The tool is nearly unusable from the description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no meaning to any parameter. Terms like 'oid', 'config_name', 'value', and 'token_ttl_seconds' are left unexplained. The agent cannot infer valid values, format, or constraints from the description alone. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Preview setting' and resource 'organization config value', indicating a preview operation for a config value. However, it does not clarify what type of config values are involved, nor does it distinguish this tool from sibling preview_set_* tools like lc_preview_set_org_quota. It is vague but not misleading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No conditions, prerequisites, or exclusions are mentioned. The agent receives no indication of when to choose this over other preview_set_ tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only mentions 'List', implying a read operation, but lacks details on behavior like pagination, filters, or side effects. With no annotations, this is insufficient disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (4 words), which is under-specified. While concise, it sacrifices necessary detail for clarity and usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and low parameter coverage, the description fails to explain the return format, the nature of Hive records, or how to use parameters effectively. It is incomplete for a tool with two parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, it does not explain the 'oid' parameter (required, but unclear if it's a parent ID) or the 'limit' parameter (default 100, but no semantics). The description adds no value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists AI skill Hive records, using a specific verb and resource. It distinguishes from sibling list tools by mentioning 'AI skill' but is not explicit about what a Hive record is.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other list tools (e.g., lc_list_ai_agents). No exclusions or prerequisites are provided, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It does not mention whether the tool is read-only, the nature of the preview, or any side effects. Critical context like authentication requirements or error states is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it sacrifices clarity and completeness for brevity. It could be expanded slightly without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and three parameters, the description is severely incomplete. It fails to explain the preview's output, behavior, or when to use it, leaving the agent without essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description adds no information about parameters. While 'oid' and 'email' are somewhat self-explanatory, 'token_ttl_seconds' is ambiguous—its purpose and format are not explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview inviting a user to an org.' conveys a verb+resource but is vague. It does not distinguish from other preview tools (e.g., lc_preview_add_group_member) and lacks clarity on what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. There is no indication of when to use this tool vs alternatives, nor any prerequisites or exclusions. The sibling list includes many preview tools, but no differentiation is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It uses 'Preview' which implies non-destructive behavior, but it does not explicitly state that no changes are made, what side effects occur, or what permissions are needed. This leaves ambiguity about whether the tool modifies state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 5-word sentence, which is concise but lacks structure and fails to provide essential details. It sacrifices clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, no annotations) and its role in a likely preview-then-confirm workflow, the description is entirely inadequate. It does not explain output, workflow integration, or how to interpret the preview result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should explain parameters. It does not mention any of the four parameters (oid, etag, channels, token_ttl_seconds) or their purpose. The channels parameter is an array of objects with additionalProperties, requiring guidance on expected structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Preview replacing ext-feedback channel configuration.' It identifies the resource (ext-feedback channels) and implies a preview action, but does not clearly define what 'preview' means in this context (e.g., validation, simulation, dry run). It distinguishes from list tools but is vague compared to similar sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lc_preview_set_feedback_channels (siblings) or lc_confirm_action. There is no mention of prerequisites, workflow steps, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not disclose behavioral traits like side effects, required permissions, or whether the tool actually performs the update or only simulates. The term 'preview' is ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is very short and to the point, but lacks structure and front-loads limited information. It is concise but at the expense of clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters, no output schema, and no annotations, the description is insufficient. It doesn't explain what the tool returns, prerequisites, or how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds no meaning to parameters. Parameter names are somewhat self-explanatory, but the description fails to explain constraints, formats, or relationships (e.g., what is 'oid', how note and verdict interact).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states it previews updating case telemetry note or verdict, specifying the action and resource. However, it doesn't clarify what 'preview' entails (simulation or actual update) and doesn't differentiate from sibling preview tools like lc_preview_update_case or lc_preview_add_case_telemetry.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_preview_add_case_telemetry or lc_preview_update_case. No context about prerequisites or selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides no behavioral details. It does not disclose side effects, error conditions, authentication requirements, or what 'resolve' entails. With no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence, but it is under-specified, lacking necessary details. Conciseness comes at the expense of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, zero parameter coverage, and minimal description, the tool is incompletely defined. An agent cannot understand return values, error handling, or resolution behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the parameter names in the schema. With 0% schema description coverage, the description should compensate but fails to explain the parameters' roles or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'resolve' and resource 'LimaCharlie authenticated resource locator'. It is distinct from similar tools like lc_get_artifact_url or lc_get_payload_download_url, though it does not explicitly differentiate from them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'Fetch,' implying read-only, but does not mention permissions, error handling (e.g., record not found), or any other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), but it sacrifices necessary detail. It is not overly verbose, but under-specification reduces its effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no parameter descriptions, the description should compensate by explaining return values or typical usage. It fails to do so, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, and the description does not explain what 'oid' or 'name' represent. Agents would need to infer the semantics, increasing risk of misuse.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Fetch one organization-note Hive record,' which clearly indicates the verb and resource. However, it does not differentiate from sibling tools like lc_get_hive_record or lc_list_org_notes, limiting clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., listing vs. fetching single, or fetching other Hive records). The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must compensate. It only states a read-like operation but lacks details on permissions, side effects, or response behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no fluff, but may be overly terse. Front-loaded but lacks necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and no parameter descriptions, the description is insufficient for an agent to understand what data is returned or how to use the 'oid' parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not mention the required 'oid' parameter or explain its meaning and format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a verb ('Fetch') and a resource ('organization usage statistics'), but is vague. Among siblings like lc_get_org_info and lc_get_billing_details, it doesn't differentiate what 'usage statistics' specifically includes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over similar get_* tools. No mention of prerequisites, context, or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'List'. It does not indicate that the operation is read-only, nor does it mention pagination, sorting, or any other behavior beyond a basic list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise, but it is under-specific. Conciseness without necessary detail is not an asset; there is no wasted text, but critical information is missing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters (one required) and no output schema, the description is too sparse. It does not explain the purpose of the parameters or the expected outcome, leaving the agent without enough context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description fails to explain any of the three parameters (oid, limit, partition_key). Users must infer their meaning from names alone, which is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool lists 'ai_memory Hive records', which is a verb+resource, but it is vague and does not differentiate from sibling tools like lc_list_ai_memories or lc_get_ai_memory_record. The exact nature of 'ai_memory Hive records' is unclear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_get_ai_memory_record for single records). There is no context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must fully disclose behavior. It states 'preview' but does not explain whether this returns a validation result, simulates creation, or has side effects. Critical details like authentication requirements or rate limits are absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no unnecessary words, but it is too brief to be effective. It lacks structure like separating purpose from behavior or parameter guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and parameter explanations, the description is insufficient. It does not provide enough context for an agent to correctly invoke the tool, especially among many similar preview tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the parameters. Parameters like 'oid', 'name', 'events', 'platforms', and 'token_ttl_seconds' are unexplained, leaving the agent unable to understand their roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview creating an exfil event rule' indicates a preview action for creating an exfil event rule, but it does not clarify what 'preview' entails or how it differs from sibling tools like 'lc_preview_create_exfil_watch'. The purpose is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not specify when to use this tool versus alternatives, nor does it mention prerequisites or contexts. This leaves the agent without guidance on selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does not state whether the tool is read-only, what side effects occur (if any), permissions needed, or what the output looks like. 'Preview' is ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence), which is concise but at the expense of critical information. It earns its place by stating the basic purpose, but additional context would not be excessive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and parameter descriptions, the description is severely incomplete. An agent cannot learn parameters, return value, or behavioral constraints from this definition alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema provides no parameter descriptions. The tool description does not explain the parameters (oid, name, token_ttl_seconds) or their purpose, leaving the agent without guidance on how to set them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview creating') and the resource ('an ingestion key'). It distinguishes from sibling tools like lc_list_ingestion_keys and lc_preview_delete_ingestion_key, but the exact meaning of 'preview' (e.g., dry-run vs. actual creation) is not clarified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like the actual creation endpoint (if exists) or other preview tools. The description does not explain the purpose of previewing or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral traits. It only states 'Preview replacing all tags' but does not disclose whether the preview is read-only, what the preview returns, how to confirm the action, error conditions, or any side effects. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 6-word sentence, which is very concise but at the expense of completeness. For a tool with multiple parameters and no schema descriptions, it should include parameter hints. It is not optimally sized given the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 required parameters, no schema descriptions, no annotations, and no output schema, the description is severely inadequate. It does not clarify the preview workflow, the difference from other tag tools, or parameter usage. An agent cannot reliably use this tool based solely on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters with 0% description coverage. The tool description does not explain any parameter (oid, tags, case_number, token_ttl_seconds). No added meaning beyond the schema, and the description fails to compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview replacing all tags on a case' clearly states the verb 'Preview replacing' and the resource 'tags on a case'. It distinguishes from sibling tools like lc_preview_add_case_tags and lc_preview_remove_case_tags by specifying 'all tags', implying a set operation. However, it does not explicitly contrast with those siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as lc_preview_add_case_tags or lc_preview_remove_case_tags. It does not mention prerequisites, typical use cases, or the two-step preview-then-confirm workflow common in preview tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks annotations, so description must disclose behavior. 'Preview' suggests dry run, but no details on side effects, auth requirements, output format, or what 'token_ttl_seconds' does. Agent cannot assess safety or expected response.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is very concise, but omits critical information. Efficiency is undermined by lack of substance. Would benefit from brief elaboration on key aspects.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 13 parameters, no annotations, no output schema, and no parameter descriptions, the description is severely incomplete. Does not explain hive record concept, preview purpose, or return value. Agent lacks sufficient context to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and description adds no parameter details. Agent sees only parameter names (oid, hive_name, key, etc.) with no hints about format, constraints, or relationships. Fails to compensate for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it previews creating or updating a Hive record. Distinguishes from delete, rename, and enabled-preview siblings. Could explicitly contrast with lc_preview_delete_hive_record to further clarify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. No when-not-to-use, prerequisites, or mention of related tools like lc_get_hive_record for reading first. Agent is left to infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description labels this as a fetch operation, implying read-only, but the presence of sync_* parameters (e.g., sync_yara, sync_exfil) raises ambiguity about potential side effects. No annotations are present, so the description fails to clarify whether setting these flags causes mutations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is short (one sentence), it sacrifices critical information. It does not adequately describe the tool's functionality given the complexity of 11 parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is severely incomplete. It lacks details about return values, parameter usage, behavioral nuances (especially regarding sync flags), and how it differs from other configuration-related tools. With no output schema and no annotations, the description fails to provide a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description does not mention any of the 11 parameters, including the required 'oid'. It provides no insight into the purpose or expected format of the parameters, leaving the agent to rely solely on the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch') and the resource ('org IaC configuration'), but the term 'IaC configuration' is somewhat domain-specific and could be ambiguous. The phrase 'through ext-infrastructure' adds context but doesn't fully distinguish from similar getter tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_org_config_value or lc_preview_push_config. There is no mention of prerequisites, or when to avoid using it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as matching behavior (e.g., case sensitivity), pagination, or whether all matching sensors are returned. This is a significant gap for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (4 words), which is efficient, but it lacks structure and substance. It does not earn its place by providing key details beyond the name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is woefully incomplete. It fails to specify return values, error behavior, or additional context needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only clarifies the 'hostname' parameter (prefix match). It does not explain the 'oid' or 'limit' parameters, leaving their meaning and usage ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find' and resource 'sensors' with the criterion 'by hostname prefix'. It distinguishes the tool from siblings like lc_list_sensors (list all) and lc_find_sensors_by_tag (by tag), though it does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lc_list_sensors or lc_get_sensor. It lacks context for selection, such as prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits such as authentication requirements, error conditions, or idempotency. For a tool with zero annotations, this is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) but at the expense of necessary detail. It does not earn its place as it provides minimal useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no output schema, and no annotations, the description is insufficient. It does not cover return value, error handling, or parameter details, leaving the agent with incomplete context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fails to explain the parameters beyond implying month and year. The oid and fmt parameters are not described, leaving the agent unsure of their meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetch') and the resource ('invoice URL') with a specific context ('for a specific billing month'). It distinguishes itself from siblings like lc_get_billing_details and lc_get_billing_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like lc_get_billing_details or lc_get_billing_status. The description does not specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It implies a read-only list operation but does not explicitly state side effects, auth needs, or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (4 words) but under-specified, sacrificing necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and one required parameter, the description fails to explain the parameter's role or distinguish the output from sibling list tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain the required 'oid' parameter; schema coverage is 0%, and the description adds no meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List exfil prevention rules' clearly states the verb (list) and resource (exfil prevention rules), but lacks differentiation from sibling tools like lc_list_dr_rules or lc_list_fp_rules.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; no prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action. It does not disclose return type, pagination (despite a limit parameter), or any behavioral traits such as whether it lists all records or requires specific permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single under-specified sentence. While short, it does not earn its place due to vagueness and lack of structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is completely inadequate. It fails to specify what the function returns, any constraints, or how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about the two parameters (oid, limit). The description must compensate but fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List lookup Hive records' uses a specific verb+resource pattern, clearly indicating it returns a list of lookup Hive records. It distinguishes from sibling tools like lc_get_lookup (single record), though it does not clarify what a 'lookup' is in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_get_lookup for a single record). The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states 'list', implying a read operation, but offers no details on side effects, permissions, or rate limits, which is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence) but this brevity comes at the cost of omitted critical information. It essentially restates the tool name without adding value, so it does not earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and low schema coverage, the description should provide far more context about return format, parameter usage, and behavior. It is completely inadequate for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description makes no mention of the two parameters (oid, limit) defined in the schema. With 0% schema description coverage, the description fails to add any meaning beyond basic name/title, leaving parameter purposes unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List SOP Hive records' specifies the verb 'list' and the resource 'SOP Hive records', clearly indicating what the tool does. However, it does not explicitly differentiate from siblings like 'lc_list_hive_records' or explain the acronym SOP, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Given the large number of sibling tools, usage hints are essential.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only mentions 'list', implying a read operation, but omits any details about authentication requirements, rate limits, data freshness, or side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short at 7 words, but this brevity comes at the cost of completeness. It front-loads the action but lacks structure or additional details that would help the agent. Overly terse without earning its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, the description is woefully incomplete. It provides no information about return format, parameter constraints, or behavior, making it nearly useless for an AI agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no meaning to the parameters. It does not explain the purpose of 'oid' (likely org ID) or 'limit' (pagination), leaving agents to infer from names alone. This is critical missing context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and the resource (YARA source names) scoped to an org. It is specific enough to distinguish from related tools like lc_list_yara_rules, though it does not elaborate on what YARA sources are.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, expected input values, or when other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description fails to disclose any behavioral traits. It does not state whether the preview is read-only, what it validates, or if it has side effects. For a 'preview' operation, this is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise, but under-specification means it does not earn its place. Better to expand with key details than remain brief but uninformative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no parameter descriptions, and no behavioral info, the description is completely inadequate. The agent cannot understand what the preview returns, how to interpret results, or whether it is safe to call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and description does not explain any parameters. Parameter names (group_id, member_oid, token_ttl_seconds) provide some semantic hints, but 'member_oid' is ambiguous (likely organization OID) and 'token_ttl_seconds' is unexplained. No additional meaning beyond names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Preview adding an organization to a group', specifying the verb (preview adding) and resource (organization to a group). Distinguishes from siblings like lc_preview_add_group_member by focusing on organization. However, it does not explain what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. No mention of prerequisites, when not to use, or related tools like lc_confirm_action. Usage is only implied by the action name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. 'Preview creating' implies a non-destructive operation, but this is not explicitly stated. No information on side effects, permissions, or return behavior is given, leaving ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only 4 words, which is overly terse. While front-loaded, it sacrifices necessary detail for brevity, missing critical guidance on usage and parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no output schema, and no annotations, the description is woefully incomplete. It fails to explain what the tool returns, how to interpret a preview, or any parameter semantics, making it nearly useless for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameter titles are the only info. The description adds no explanation for any of the 6 parameters (oid, name, module, data_type, config, token_ttl_seconds), leaving their purpose and constraints completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The phrase 'Preview creating an output integration' clearly identifies the verb (preview creating) and resource (output integration), distinguishing it from other preview tools for different resources. However, it does not clarify what 'preview' entails (e.g., validation, simulation) or how it relates to actual creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_list_outputs or actual creation endpoints. The description lacks any mention of prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must fully disclose behavior. It only says 'Preview deleting' without explaining whether it mutates state, returns a summary, or requires confirmation. The term 'preview' suggests read-only but is ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief (4 words) but lacks essential information, making it under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 parameters, no parameter descriptions, no output schema, no annotations), the description is woefully incomplete. It fails to explain the preview behavior, parameter meanings, or expected return.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description provides no information about the three parameters (oid, name, token_ttl_seconds). The agent cannot infer what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it previews deleting an artifact collection rule, which is a specific verb and resource. It clearly distinguishes the resource from other preview delete tools, but it does not explain what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when-not to use, or related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. 'Preview' suggests a simulation but is not explicit about side effects, permissions, or output. Lacks detail on behavioral traits beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely short (4 words), but this is under-specification rather than conciseness. Does not provide essential context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and 3 undocumented parameters. For a preview tool, the description should indicate what the preview returns or how it affects state. Totally inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description adds no information about parameters (oid, name, token_ttl_seconds). Agent cannot infer what each parameter means from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Preview deleting' and the resource 'a false-positive rule,' which is clear. However, it does not differentiate from siblings like lc_preview_set_fp_rule or lc_get_fp_rule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not explain what 'preview' means or when a preview is needed over actual deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not explain what 'preview' entails (e.g., whether it simulates or actually performs the deletion, or what side effects occur). Minimal disclosure beyond the verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very brief (one sentence), but under-specification sacrifices useful detail. Not concise in the sense of being efficient; rather, it is insufficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters, no output schema, and no description of return values or behavior, the description is incomplete for an agent to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no meaning to the parameters oid, name, or token_ttl_seconds. The agent cannot infer their purpose from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting an ingestion key' clearly states a specific verb (preview delete) and resource (ingestion key), distinguishing it from sibling preview tools for other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_preview_delete_api_key or lc_delete_ingestion_key. Lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a non-destructive preview, but does not disclose what the preview returns, side effects, or required permissions. With no annotations, the description fails to adequately convey behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short, but at the cost of missing critical information. It does not earn its place by being informative; it is under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter documentation, the description is far from complete. It does not explain the preview's behavior, return value, or parameter roles, making it insufficient for correct tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters (oid, token_ttl_seconds, installation_key_id) are undocumented in both the schema and the description. The description adds no meaning to the parameter names, leaving their purpose and format unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview deleting) and the resource (installation key). It distinguishes itself from sibling tools by the specific resource name, but does not explain what 'preview' entails compared to other preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as lc_get_installation_key or actual deletion tools. No prerequisites or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a preview (non-destructive) operation but does not explain what the preview returns (e.g., a token, summary), whether it requires special permissions, or any side effects. Without annotations, the description lacks necessary behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but too sparse for a tool with three parameters and no schema coverage. It sacrifices essential detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the number of parameters, lack of annotations, and presence of many sibling preview tools, the description is grossly incomplete. It does not cover prerequisites, return values, or the overall workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the three parameters. The schema has no descriptions, so the agent is left without context on what 'oid', 'job_id', and 'token_ttl_seconds' represent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'preview deleting' and the resource 'service job record', which is specific. However, it does not differentiate this from other preview delete tools in the sibling list, lacking explicit context about what makes this tool unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention that it is a dry-run before confirming deletion, nor does it indicate any prerequisites or associated confirmation steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description merely states the action is a 'preview'. It does not disclose the behavioral impact (e.g., whether it is safe, what happens to the token, or if any state is modified). The mention of a 'confirmation token' hints at a process but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, very short sentence (10 words). While concise, it omits essential details and does not front-load the most critical information. The brevity harms usability rather than aiding clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotations, and minimal parameter descriptions, the description is severely incomplete. It fails to explain the preview process, the role of the token, or what the tool returns, leaving the AI agent without sufficient context to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description only vaguely references the 'confirmation token' without explaining the parameters 'oid' or 'token_ttl_seconds'. The description adds no meaningful context beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'preview deleting' and the resource 'an organization', which is distinct from other lc_preview_delete_* siblings by the resource name. However, it does not elaborate on what 'preview' entails, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not specify prerequisites, such as obtaining a confirmation token first, or when previewing deletion is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear the full burden of behavioral disclosure. It only says 'Preview sending,' which is ambiguous—it does not clarify if this action actually sends a request or simply simulates it. No information on permissions, side effects, or rate limits is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise, but it is under-specified. It lacks essential details that should be included. True conciseness would provide adequate information in a compact form; this description sacrifices clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has high complexity (12 parameters) and no annotations or output schema, yet the description is only 8 words. It fails to explain what 'preview' entails, the purpose of the parameters, or what the tool returns. The description is wholly inadequate for an agent to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 12 parameters with 0% description coverage, and the tool description adds no explanation for any parameter. The parameter names alone (e.g., oid, channel, question) are insufficient for an agent to understand how to use them correctly. This is a critical deficiency.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview sending) and the resource (external approval request via ext-feedback). The tool name also reinforces this. However, it does not explicitly differentiate from sibling preview tools for feedback (e.g., preview_feedback_acknowledgement, preview_feedback_question), which lowers the score slightly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool versus alternatives, nor does it mention any prerequisites or conditions. This is a significant gap given the number of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The word 'preview' implies it does not execute the removal, but the description does not explicitly state that no changes are made, what the output looks like, or any other behaviors. With no annotations, the description carries full burden and falls short.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, but it is under-specified. While concise, it does not provide enough information to be useful, making it closer to a tautology.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a preview tool with no output schema, the description should explain what the preview returns and how to interpret it. It is incomplete, leaving the agent without essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not add any parameter-specific meaning beyond the schema. It does not explain email format, group_id context, or token_ttl_seconds purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'preview removing' and the resource 'user from group members'. It distinguishes from sibling tools like 'lc_preview_add_group_member' and 'lc_preview_remove_group_owner' by specifying the action and target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention that it should be used before a real removal, nor does it compare to other preview or action tools. Lacks prerequisites like requiring the user to be a member.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'preview removing' but does not clarify that this is a dry-run with no actual changes, nor does it mention required permissions, rate limits, or what the output represents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but lacks essential details. It is concise in length but underspecified, making it insufficient for an agent to understand the tool fully. Every sentence should earn its place; here it does not provide enough value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 parameters, no output schema, no annotations), the description is severely incomplete. It does not mention what the preview returns, the effect of token_ttl_seconds, or any prerequisites. The tool likely requires specific permissions, but that is absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the three parameters (oid, email, token_ttl_seconds). With 0% schema description coverage, the description fails to add meaning beyond the parameter names. For example, 'token_ttl_seconds' is not described.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('preview removing a user from an org') which matches the tool name. It is specific about the verb and resource. However, it does not differentiate from sibling preview tools like lc_preview_remove_group_member, which also involve removal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description implies its use case but does not give context or exclusions, such as needing to use lc_preview_remove_user_permission for removing permissions instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It states 'preview' but does not explain what the preview entails (e.g., whether it is idempotent, returns a diff, or requires specific permissions). The lack of output schema further obscures behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is minimal, but it is under-specification rather than conciseness. It lacks critical details needed for correct tool usage, harming overall efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no annotations, no output schema, and many sibling preview tools, the description is completely inadequate. It does not explain the preview output, relationship to other hive tools, or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate by explaining parameters. It fails to do so; 'new_name' and 'key' are not described. The agent has no semantic guidance beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview renaming') and the resource ('generic Hive record'). However, it does not differentiate from sibling preview tools like lc_preview_set_hive_record or lc_preview_delete_hive_record, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as the actual rename tool (not shown) or other preview tools. There is no mention of prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It indicates a preview (non-destructive) but doesn't disclose auth needs, side effects, or return format. The cryptic 'partial-merge hook' adds no behavioral clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (one short sentence), but it lacks necessary detail. The description is too minimal to be useful, failing to explain core concepts like 'partial-merge hook'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters (4 required), no output schema, and no annotations, the description is grossly insufficient. It fails to cover parameter semantics, return values, or behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not mention any of the 6 parameters (oid, agent, content, memory_name, partition_key, token_ttl_seconds), leaving the agent completely uninformed about their meaning or required values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it previews setting one ai_memory entry via a partial-merge hook, which clearly identifies the action and resource. However, the term 'partial-merge hook' is not explained, and it does not differentiate from sibling preview tools like 'lc_preview_set_ai_agent'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, context, or exclusions. Given the many preview siblings, this is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The term 'Preview' implies a dry-run, but the description does not explain what the preview entails (e.g., validation, side effects, or response format). Without annotations, the behavioral traits are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While very concise, the single sentence is insufficient for a tool with 8 parameters. It sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and 8 parameters, the description is woefully incomplete. It does not explain the output or the distinction between creating and updating.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the 8 parameters. The agent receives no help understanding 'oid', 'patterns', or other fields beyond their names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool previews creating or updating an artifact collection rule, which is specific and distinct from delete operations. However, it doesn't differentiate among multiple 'set_' preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about when a preview is necessary or how it compares to actual creation/update.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It implies a non-destructive preview, but it does not state whether it requires special permissions, if it modifies state, or what the output (e.g., success indicator or diffs) looks like. The minimal description leaves significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it underspecifies the tool's behavior and parameters. It lacks front-loaded critical information and fails to earn its place by providing insufficient value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters (including a nested object), no output schema, and no annotations, the description is severely incomplete. It does not explain what the tool returns, how the preview works, or what the config object should contain. The tool requires substantial additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It does not mention any parameter names or roles. The 'config' object (which accepts any properties) remains entirely undefined, and 'oid' and 'token_ttl_seconds' are not described.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Preview replacing Cases configuration for an org,' which clearly indicates the action (preview) and the resource (Cases configuration). It distinguishes itself from direct set tools (like lc_set_cases_config?) and retrieval tools (lc_get_cases_config) by emphasizing 'preview.' However, it does not explicitly differentiate from other preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No prerequisites, when-not-to-use, or comparison with sibling tools is provided. The description is too brief to inform decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. The word 'Preview' suggests no side effects, but this is not explicitly stated. There is no mention of safety (e.g., destructive potential), permissions required, or what happens to the rule after preview.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence) but insufficiently informative. Conciseness should not come at the expense of clarity; here, critical details are omitted, making it under-specified rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high parameter count (10), required nested objects, and lack of output schema, the description is woefully incomplete. It fails to provide any context about the 'data' object structure, return values, or how to construct valid input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no meaning to any of the 10 parameters. It does not explain what 'oid', 'data', 'etag', 'tags', etc., represent, leaving the agent to rely solely on schema titles which are minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview') and the resource ('creating or updating a D&R rule'). It distinguishes from sibling preview tools that target other rule types (e.g., FP rules, integrity rules) by explicitly naming D&R rules.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are many preview_set_* siblings but no mention of when preview is appropriate versus an actual set operation. The description does not clarify if this tool actually commits changes or only simulates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It indicates 'preview' but does not explicitly confirm that no side effects occur (e.g., simulated dry run). Missing details on validation behavior, error conditions, or return value nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 11 words, which is too brief for a tool with 10 parameters and no annotations. It sacrifices essential information for brevity, resulting in under-specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 params, no annotations, no output schema), the description is woefully incomplete. It fails to explain what an external adapter is, how preview differs from actual set, or what the response contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description does not explain any of the 10 parameters (oid, name, data, etc.). The agent must infer meanings from names alone, which is insufficient given the complexity and lack of enums.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool previews creating or updating an external adapter Hive record. The verb 'preview' and resource 'external adapter' are specific, and the action 'creating or updating' is explicit. However, it does not distinguish from sibling preview tools for other resources, but the resource name provides differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lc_preview_set_external_adapter_enabled or the actual set operation. There is no mention of prerequisites, context for use, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It states 'preview toggling' but does not confirm that no modifications occur (i.e., it's a safe read-only operation). It also lacks information about required permissions, side effects, or response format, leaving the agent uncertain about the tool's impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, but it sacrifices necessary details. While brevity is good, the lack of structure (e.g., separate sections for behavior, parameters, output) makes it hard for an agent to parse quickly. It would benefit from additional context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters, no output schema, no annotations), the description is woefully incomplete. It fails to mention that this is a dry-run operation, what the output represents, or the meaning of each parameter. The agent has insufficient information to correctly select and invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage on parameter names but 0% descriptions. The tool description adds no explanation for 'oid', 'name', 'enabled', or 'token_ttl_seconds'. For example, it's unclear whether 'oid' refers to the Hive record OID or the external adapter OID. This forces the agent to rely on schema names alone, which are insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for previewing a toggle of the enabled metadata of an external adapter Hive record. It uses a specific verb 'preview toggling' and identifies the resource 'external adapter Hive record's enabled metadata', distinguishing it from other preview tools for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It does not mention that this is a dry-run operation (no changes are made), nor does it explain prerequisites like the existence of the external adapter. This is a critical gap for a preview tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral info. 'Preview' implies non-destructive, but it doesn't explicitly state that no actual changes are made, what side effects occur, or any permissions needed. The term 'preview' is ambiguous without elaboration.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase, but it is under-specified, not concise. It omits essential context and would benefit from additional sentences to improve clarity without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complex input schema (nested objects, 9 parameters), no output schema, and no annotations, the description is critically incomplete. It does not explain the preview behavior, return value, or any constraints, leaving the agent with insufficient information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description provides zero parameter information. It does not explain what 'oid', 'data', 'name', 'etag', etc. mean, nor does it clarify the expected structure of the 'data' object. This is insufficient for an agent to correctly fill parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'preview' and the resource 'false-positive rule', distinguishing it from sibling preview_set tools by resource type. It could be more explicit about what 'preview' means (e.g., dry-run without applying changes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Among many lc_preview_set_* siblings, there is no context explaining that this is for previewing a false-positive rule change before committing, or what distinguishes it from other similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavior. It mentions 'preview creating or updating' but does not clarify that this is a dry run, that no actual changes occur, or what the output looks like. Side effects, permissions, and return format are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is concise at 12 words, but it is under-specified and lacks detail. Every word is necessary, but more information is needed about the tool's behavior and parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters, no output schema, and no annotations, the description is severely incomplete. It does not provide enough context for an AI agent to correctly invoke the tool, such as what the preview returns or what constraints exist on parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description explains none of the 10 parameters. It fails to compensate for the lack of schema descriptions. Required parameters like 'oid', 'name', and 'data' are not explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Preview creating or updating an organization-note Hive record,' which specifies the verb ('preview creating/updating') and resource ('organization-note Hive record'). It is clear and consistent with sibling 'preview_set_*' tools, but could be more explicit about what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_set_org_note or lc_get_org_note. There are many sibling 'preview_set_*' tools, and the description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only says 'Preview' which implies a dry-run, but no details about what the preview entails, what it returns, side effects, or required permissions. Without annotations, the description fails to disclose important behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only one sentence, which is concise but at the expense of essential information. It is under-specified and does not earn its place as it lacks detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description is grossly insufficient. The agent cannot understand the tool's behavior or correctly invoke it without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not mention any parameters. The agent receives no guidance on what parameters like oid, name, source, or token_ttl_seconds mean or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool is for previewing creating or updating a YARA source. It clearly identifies the action (preview) and the resource (YARA source). However, it does not differentiate from other preview tools like lc_preview_set_yara_rule, but the resource is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as lc_get_yara_source or lc_list_yara_sources. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The term 'preview' implies a read-only, non-destructive operation, but no explicit confirmation or additional behavioral details are given. With no annotations provided, the description fails to clarify whether permissions are checked, what format the preview output takes, or if any state is affected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 4-word sentence, which is concise but severely under-specified. It lacks any structure that would help an agent quickly parse key information, such as bullet points or distinct sections for purpose, usage, or parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is highly incomplete given the tool's complexity (3 parameters, no output schema, no annotations). It does not define 'unsealing', explain the preview mechanism, or provide any context about return values or side effects, leaving the agent with insufficient information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the three parameters (oid, sensor_id, token_ttl_seconds). Given 0% schema description coverage, the description should compensate but adds no meaning beyond the parameter names. The agent has no insight into what these values represent or how they affect the operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview unsealing') and the resource ('one sensor'), which aligns with the tool name. However, it does not differentiate this tool from its sibling 'lc_preview_seal_sensor' or other preview tools, missing an opportunity to clarify the specific scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'lc_preview_seal_sensor' or 'lc_get_sensor_seal_status'. The description does not indicate prerequisites or conditions for use, leaving the agent without contextual decision-making support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It implies a non-mutating preview but does not confirm safety, mention required permissions, or describe return format. The word 'preview' suggests dry-run, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is short at one sentence, it omits essential information. It is not well-structured because it fails to front-load the most critical details (e.g., that this is a dry-run, how parameters work).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is severely incomplete. It does not explain the tool's behavior, return values, or parameter semantics. For a tool with three parameters, this level of description is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation for any of the three parameters (oid, extension_name, token_ttl_seconds). An agent must rely solely on parameter names, which are insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview unsubscribing) and the resource (org from an extension). It distinguishes from sibling tools like lc_preview_subscribe_extension. However, it does not explain what 'preview' entails, which could lead to ambiguity about whether it is a dry-run or an actual action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_preview_subscribe_extension or lc_preview_delete_extension. The description lacks context about prerequisites or typical scenarios for using this preview.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description does not explain that 'preview' implies a non-destructive simulation, which is critical for an agent. No mention of side effects, permissions, or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief (one sentence), but brevity here sacrifices necessary detail. It is not concise in a helpful way; it is under-specified. The sentence could be expanded to include key behavioral details without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of any output schema, parameter descriptions, and annotations, and the presence of five parameters including a token_ttl_seconds field, the description is woefully incomplete. The agent lacks essential context to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema provides no parameter explanations. The description adds no information about any of the five parameters (oid, case_number, event_id, is_public, token_ttl_seconds). The agent cannot infer what these mean or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it previews changing a case note's public visibility, which is a specific verb and resource. It clearly differentiates from other preview tools like 'preview_add_case_note' or 'preview_update_case' by focusing on visibility. However, it doesn't clarify what 'preview' means (e.g., dry-run vs. actual change), which limits clarity slightly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Among many similar preview tools, there is no distinction or context provided. The agent has no help in deciding between this and, say, 'lc_preview_update_case' or 'lc_preview_add_case_note'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It states 'Dry-run', implying no side effects, but does not confirm read-only nature, authentication needs, or rate limits. No mention of return format or errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks substance. It is front-loaded but sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 9 parameters, 2 required, no output schema, and high complexity, the description is severely incomplete. It fails to explain parameter relationships, return values, or execution behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of any parameter. Essential fields like 'events', 'oid', and 'rule_content' are not described, leaving the agent without understanding their purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a dry-run of a D&R rule against explicit events, using the verb 'Dry-run' and specifying the resource 'D&R rule'. It distinguishes from siblings like lc_replay_dry_run by mentioning 'explicit events', but could more explicitly differentiate from lc_validate_replay_rule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_replay_dry_run or lc_validate_replay_rule. The description lacks context on prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits, but it only states the basic function. It does not mention read-only nature, rate limits, pagination, or what the tool does with the search results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but too brief. It lacks necessary detail, so it does not earn its place despite being front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and three thoroughly undocumented parameters, the description is completely inadequate. An agent cannot determine how to properly invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description should explain the parameters. However, it does not mention any of the three required parameters (oid, entity_type, entity_value) or their purpose, leaving the agent without necessary context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Search' and the resource 'case entities' with scope 'across an org'. It distinguishes from the sibling 'lc_list_case_entities' which likely lists entities for a specific case, though it could be more specific about the search criteria.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'lc_list_case_entities' or when to search by entity type/value. The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It mentions 'lookup' implying a read operation, but lacks details on side effects, output format, or constraints like pagination. Minimal behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks necessary detail. It is not verbose, but the brevity sacrifices clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 params, nested objects, no output schema, no annotations), the description is severely incomplete. It fails to explain required fields, parameter formats, or expected behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no information about any of the 5 parameters. The agent cannot infer what 'oid', 'objects', 'info', 'limit', or 'case_sensitive' mean from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it does batch lookup (prevalence or location) for IOC groups, distinguishing it from the singular lc_search_ioc sibling. However, 'bounded' is ambiguous and could be clarified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like lc_search_ioc. The term 'batch' implies multiple IOCs, but no when-not or alternative information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks disclosure of side effects, error conditions (e.g., token expiration), or idempotency. Since no annotations are provided, the description carries the full burden, but it only offers a vague 'execute' without behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, which is efficient but omits critical context. It could pack more useful information without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter, no output schema, and no annotations, the description is incomplete. It does not explain the overall workflow (preview then confirm) or how the token is obtained, leaving agents without sufficient context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'confirmation_token' is only described as a 'short-lived preview token' without details on format, origin, or validation. With 0% schema description coverage, the description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'execute' and specifies the resource 'action bound to a preview token'. It clearly indicates that this tool performs a confirmation step, though it could explicitly state that it confirms a preview action from a sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_cancel_action. The description does not mention prerequisites, such as needing a preview token from a previous lc_preview_* call.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavior. It only says 'explain', but does not mention any prerequisites, side effects, or what happens when parameters are omitted. Behavior is under-specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is too brief and lacks structure. It could be slightly expanded to include parameter usage without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of four parameters with no schema descriptions and no output schema, the description is grossly incomplete. It does not explain how to use the tool or what to expect in return, making it inadequate for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description fails to explain any of the four parameters (profile, operation, permission, error_message). With 0% schema coverage, the agent has no guidance on how to populate these fields to get a useful explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb 'explain' and the resource 'LimaCharlie permissions and missing-permission failures'. It distinguishes from sibling tools like lc_list_user_permissions which list rather than explain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as lc_list_user_permissions or other diagnostic tools. The context of use is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden, but it only states the basic function. It does not disclose if results are paginated, ordered, or limited, nor any authentication or rate-limiting behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with no wasted words, but it could include more detail without losing conciseness. It achieves minimal length but at the cost of informativeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain the output format, result limits, or prerequisite context, making it inadequate for correct tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no meaning to parameters like 'oid' or 'tag.' The 'oid' is required but unexplained; 'limit' is default to 100 but not clarified. This leaves ambiguity for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find' and the resource 'sensors with a specific tag,' indicating a filtered retrieval operation. However, it does not distinguish this tool from sibling tools like lc_find_sensors_by_hostname or lc_list_sensors, limiting clarity for selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_list_sensors or lc_find_sensors_by_hostname. The description implies a use case (finding by tag) but offers no exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It implies a read operation but provides no details on side effects, error behavior, or required permissions. The phrase 'fetch one memory entry' is too vague to be fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 10 words, which is concise. However, given the lack of parameter explanations and behavioral context, the brevity results in under-specification rather than efficient communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters, no output schema, no annotations, and is part of a large set of sibling tools. The description fails to provide essential context such as what constitutes a memory entry, how partition_key is used, or the relationship to other AI memory tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to any of the 4 parameters. It does not explain what each parameter represents or how they should be used, leaving the agent to rely solely on parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (fetch) and the resource (one memory entry from an ai_memory agent record). However, it does not differentiate from the similarly named sibling lc_get_ai_memory_record, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_list_ai_memories or lc_get_ai_memory_record. The description only states what it does, not the context for its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states 'request', implying read-like behavior, but does not mention side effects, authentication, rate limits, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise, but it sacrifices essential information. It is appropriately sized for a simple retrieval tool but lacks completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and two undocumented parameters, the description is far from complete. It does not explain return values, behavior, or provide enough context for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain the meaning of the two required parameters ('oid' and 'artifact_id'). Schema coverage is 0%, and the description fails to compensate with any parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Request original artifact payload or signed export URL' clearly states the action (request) and resource (artifact payload or URL). It distinguishes from sibling tools like 'lc_list_artifacts' (listing) and 'lc_get_payload_download_url' (getting download URL), though it could be more explicit about the difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'lc_get_payload_download_url' or 'lc_list_artifacts'. The description lacks context about prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose read-only nature, rate limits, or what the counts represent. The minimal description adds no behavioral context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence), which is concise, but lacks substance. It sacrifices necessary detail for brevity, making it insufficiently informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter, no output schema, and no annotations, the description is incomplete. The agent cannot understand the return format, what counts are included, or how to use the output. More detail is needed for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'oid' is solely named; its purpose is unclear (org ID? case ID?). Schema coverage is 0%, and the description provides no additional meaning. The agent cannot infer what value to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it gets dashboard counts for cases, which is a specific purpose. It distinguishes from siblings like lc_get_case and lc_list_cases by implying aggregated counts. However, it could be more precise about what 'dashboard counts' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Among many get/list siblings, the description does not specify context or prerequisites, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It only states 'Fetch', implying a read operation, but does not mention idempotency, authentication requirements, rate limits, or potential errors. Insufficient disclosure for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), but it sacrifices content. It is under-specified rather than efficiently informative. It fails to earn its place by omitting critical details that could fit in the same space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema, no annotations), the description should cover parameter roles, return value, and behavior. It does none of these. It is incomplete for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters 'oid' and 'name'. It adds no meaning beyond the parameter names from the schema. The agent is left to infer their purpose, which is inadequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one cloud adapter Hive record' clearly states the action (Fetch) and resource (cloud adapter Hive record). It distinguishes from sibling tools like lc_list_cloud_adapters (list all) and lc_set_cloud_adapter (create/update) by implying single record retrieval. However, it does not elaborate on what constitutes a cloud adapter or the meaning of 'Hive record', which is slightly vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_list_cloud_adapters or lc_preview_set_cloud_adapter. There is no mention of prerequisites, context, or exclusions. The description lacks any usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It only states the function without explaining what 'extension definition' entails, whether it requires authentication, or potential side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, very concise. It is front-loaded but lacks structure for clarity. While concise, it could benefit from additional detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and a simple parameter, the description is incomplete. It does not describe the return value, error conditions, or how the response relates to other tools. An agent would need additional context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter, extension_name, with no description. The tool description does not explain this parameter or how to determine its value. With schema coverage at 0%, the description adds no semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one globally available extension definition' clearly identifies the verb (Fetch) and resource (extension definition). It specifies 'one' and 'globally available', which distinguishes it from sibling tools like lc_list_available_extensions (list all) and lc_get_extension_schema (schema for an extension). However, it does not explicitly contrast with these siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_extension_schema or lc_list_available_extensions. There is no mention of prerequisites, context, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like read-only nature or authorization needs. It only states 'Fetch', implying read-only, but does not confirm side effects or response structure. More detail needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it sacrifices necessary detail. It is not front-loaded with key information; it's too brief for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the two required parameters, no output schema, and no annotations, the description is incomplete. It should explain what an extension schema is, what the parameters mean, and what the return value will be. The current description leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the parameters. It does not explain what 'oid' or 'extension_name' represent, beyond the implied org context. The parameters are completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Fetch' and specifies 'one extension schema for an org context', making the tool's purpose clear. However, it does not explicitly distinguish from similar tools like lc_get_extension, but the name and phrasing imply a specific resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_get_extension or lc_list_available_extensions. The description lacks context about prerequisites or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states the action without disclosing any behavioral traits (e.g., read-only nature, required permissions, side effects). The agent has no additional context beyond the function name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence). However, it is too minimal for the tool's complexity, lacking parameter explanations and usage context. Conciseness is achieved at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With four parameters, no output schema, and no annotations, the description provides minimal context. It does not explain what metadata is returned, how to use the parameters, or how this tool fits with other Hive-related tools. The description is incomplete for an agent to confidently select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about any of the four parameters (key, oid, hive_name, partition_key). The agent must guess their meaning from parameter names alone, which is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch') and the resource ('one Hive record's metadata'). It distinguishes from sibling tools like 'lc_get_hive_record' and 'lc_get_hive_schema' by specifying 'metadata' rather than the record itself or its schema. However, it could be more precise about what constitutes metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'lc_get_hive_record' or 'lc_get_hive_schema'. The agent is left to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only says 'Fetch' which implies read-only, but does not explicitly state that it is non-destructive, nor does it mention auth requirements or rate limits. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) but it is front-loaded and free of fluff. However, it is arguably too brief and does not provide enough context, bordering on under-specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and no annotations, the description should explain what a 'typed Hive' is and what the returned JSON Schema represents. It fails to do so, leaving the agent without enough information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description adds no meaning beyond the input schema. The hive_name parameter is not described at all (e.g., what constitutes a valid name, where to find it). The description fails to compensate for the lack of schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'JSON Schema for a typed Hive', making the purpose understandable. However, it does not differentiate from sibling tools like lc_get_hive_record or lc_list_hive_types, which could lead to confusion for an AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no exclusion criteria, and no context for when the tool is appropriate. An agent would not know to prefer this over other get/list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It only says 'request', implying a read operation, but does not disclose whether this action has side effects, requires specific permissions, or if the token has an expiry. No behavioral context is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and to the point. It delivers the essential information without extra words, so it earns a high score for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no output schema), the description is incomplete. It does not explain what the token looks like, how to use it, or if any error conditions exist. More context is needed for safe usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description adds no meaning to the single parameter 'oid'. It does not clarify that 'oid' refers to the organization ID, leaving the parameter undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: requesting a deletion confirmation token for an organization. It uses a specific verb ('request') and resource ('organization delete confirmation token'), which distinguishes it from sibling tools like lc_delete_org that perform the actual deletion. However, it could be more explicit about being a prerequisite step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention that this token is needed before calling lc_delete_org, nor does it specify any prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read operation via 'Fetch,' but with no annotations, it fails to disclose other behavioral traits such as permission requirements, performance characteristics, side effects, or response format. The lack of detail leaves the agent with minimal understanding of the tool's behavior beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, making it concise and front-loaded. However, it is too sparse, omitting critical details. While there is no wasted text, the brevity sacrifices information, resulting in an adequate but not optimal balance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and minimal parameter documentation, the description is grossly incomplete. It does not specify what the returned data contains, any constraints (e.g., only one org at a time), or error conditions. This severely limits the agent's ability to correctly use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description does not explain the 'oid' parameter. The description mentions 'for an explicit org' but does not connect it to the parameter. The agent receives no semantic help beyond the parameter name, leaving it unclear how to provide the correct value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'enforced quota usage for an explicit org.' This distinguishes it from sibling tools like lc_get_org_info or lc_get_billing_details. However, it does not elaborate on what 'quota usage' encompasses, such as limits or current usage, which could be ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lc_get_org_info or lc_get_org_stats. There is no mention of prerequisites, exclusions, or context that would help an agent decide to invoke this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits itself. It only states 'fetch' but does not mention that it is read-only, whether authentication is required, or what the response contains. This is insufficient for an agent to understand its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (5 words), which is good, but it lacks necessary detail. It is front-loaded but under-specified, providing minimal value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool requires two parameters and has no output schema, the description should offer more context about what an event schema is and how it relates to other schema tools. It is incomplete for effectively selecting and invoking the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the required parameters 'oid' and 'name'. The agent cannot infer what these parameters represent, which severely impacts correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one event schema definition' clearly states a specific verb and resource ('event schema'), and the inclusion of 'event' distinguishes it from sibling tools like lc_get_extension_schema and lc_get_hive_schema. However, it is very brief and could be more explicit about the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_list_schemas or lc_get_extension_schema. The description does not specify prerequisites or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only says 'check,' implying a read-only operation, but does not confirm no side effects, required permissions, or whether the check is instantaneous. Minimal transparency beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is underspecified. It adds no structure or additional detail beyond the tool name. For a simple tool, this is adequate but not exemplary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and 0% parameter coverage, the description is too brief. It does not explain the return value (boolean? status string?), possible errors, or any edge cases (e.g., sensor not found). The tool is simple, but completeness is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation for the two required parameters (oid and sensor_id). The agent is left to infer their meanings from names alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Check' and the resource 'whether one sensor is currently network-isolated,' making the purpose straightforward. It distinguishes from sibling tools like lc_get_sensor and lc_get_sensor_seal_status by specifying the isolation status check. However, it does not explicitly mention the return type (e.g., boolean).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives such as lc_get_sensor (which may include isolation status) or lc_preview_isolate_sensor (which changes isolation). The description lacks context about prerequisites, such as requiring sensor isolation to be enabled.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral traits. It does not disclose if the operation is read-only, authentication needs, error behavior, or rate limits. The minimal description fails to provide transparency beyond the basic fetch action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise. However, it is too brief to be useful, sacrificing necessary detail for brevity. The structure is fine but under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters (2 required), 0% schema coverage, no output schema, and no annotations, the description is severely incomplete. It does not explain the return format, the required organization ID (oid), or the purpose of the days parameter. The tool's complexity demands far more detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning beyond parameter names. It mentions 'one CVE' but does not explain the required 'oid' parameter or the 'days' default. No parameter-level descriptions are provided, leaving critical context for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches 'EPSS score and percentile history for one CVE', specifying the action and resource. It distinguishes from siblings like lc_get_vulnerability_cve (likely CVE details) and lc_list_vulnerability_cves (list of CVEs), though explicit sibling differentiation is absent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, when not to use it, or any prerequisites. The description merely states the action without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only says 'List AI agent Hive records' without mentioning permissions, side effects, limits, or pagination. The required 'oid' parameter is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and is front-loaded, but it is too brief and omits critical details, sacrificing completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two parameters (one required), no output schema, and no annotations, the description is inadequate. It does not explain the parameters or the return value, leaving the AI agent with insufficient context to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the schema. With 0% schema coverage, parameters 'oid' and 'limit' are undocumented. The description does not clarify that 'oid' likely filters by organization or that 'limit' controls record count.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and the resource (AI agent Hive records), distinguishing it from sibling tools like lc_list_ai_memories or lc_list_ai_sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_ai_agent or other list tools. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully describe behavior. It only states 'list memory entries,' lacking details on whether it returns all entries, pagination, or any side effects. It is a minimal behavioral hint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but at the cost of necessary detail. It is front-loaded but under-informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and no output schema or annotations, the description is incomplete. It omits details about return format, parameter semantics, and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description provides no explanation for the three parameters (oid, agent, partition_key). The agent name fails to clarify their roles or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (memory entries for an ai_memory agent record). It is specific and distinguishes from siblings like lc_get_ai_memory but does not explicitly differentiate from lc_list_ai_memory_records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_get_ai_memory or lc_list_ai_memory_records. No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It fails to disclose behavioral traits like pagination, rate limits, auth requirements, or that it is a read-only operation. The 'limit' parameter implies pagination but is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but lacks informative content beyond the name. It is not wasteful but fails to add value, making it minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not cover what is returned, parameter details, or usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the 'oid' and 'limit' parameters. The description must compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it lists API key metadata for an org, providing a specific verb and resource. It is clear but does not differentiate from sibling list tools like lc_list_installation_keys or lc_list_ingestion_keys.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_preview_create_api_key or other list tools. No exclusions or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present; description fails to disclose behavioral traits like read-only nature, authentication requirements, or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but omits necessary details, making it under-informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, description should clarify return value but does not; minimal details provided for a listing operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one parameter (limit) with no description; tool description adds no meaning, and schema coverage is 0%, leaving the agent uninformed about the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List globally available extension definitions,' specifying verb and resource. However, it doesn't explicitly distinguish from siblings like lc_list_extension_subscriptions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_get_extension or lc_list_extension_subscriptions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It implies a read operation but does not disclose any behavioral traits such as permissions needed, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) but lacks important context. It is concise but at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description does not indicate what data is returned. The description is insufficient for an agent to understand the tool's behavior fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain the meaning of 'oid' (likely org ID) or 'limit', leaving the agent to infer from parameter names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (services/replicants) and specifies the scope (available to an org). It is specific but does not differentiate from numerous sibling list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_list_orgs or lc_list_sensors. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only conveys a read operation but lacks any disclosure of behavioral traits such as authentication needs, rate limits, or side effects. Since no annotations are provided, the description carries full burden and falls short.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) and front-loaded, but it is overly minimal and lacks any structural elements like context or parameter hints. It is acceptable for a simple list tool but does not add value beyond the name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool requires two parameters with no schema descriptions and returns an unspecified output, the description is incomplete. It fails to explain what telemetry references are or how the parameters relate to the case, leaving ambiguity for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of what 'oid' or 'case_number' represent. The description adds no meaning beyond the parameter names, leaving agents to infer their roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and resource 'telemetry references' with scope 'linked to a case'. It implicitly distinguishes from sibling tools that list other case-related items (e.g., artifacts, detections) by focusing on telemetry references.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_list_case_artifacts or lc_list_case_detections. No prerequisites or context for use are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Minimal description with no annotations. Does not disclose if read-only, response format, or any side effects. Even a listing tool would benefit from stating it's safe or read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise but lacks structure. While short, it could be improved with a more informative sentence that covers purpose and key constraints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is critically incomplete. It does not explain return values, parameter meanings, or any contextual details needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds no information about parameters (oid, limit) beyond their names and types in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'cloud adapter Hive records', distinguishing it from sibling tools like lc_list_hive_records which are more generic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like lc_get_cloud_adapter or lc_set_cloud_adapter. No context on prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states the action without disclosing behavioral traits such as read-only nature, authorization requirements, or parameter-driven behavior. With no annotations, the description should provide more context but fails to do so.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), which is positive for brevity, but it sacrifices necessary detail. It could be improved by adding parameter explanations while remaining concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and no annotations or output schema, the description is insufficient. It does not cover return values, pagination, or the meaning of required versus optional parameters, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema parameters are not documented in the schema. The description does not explain any of the parameters (oid, limit, namespace), leaving the agent without guidance on how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists D&R rules from a hive namespace, using a specific verb 'List' and resource 'D&R rules'. The abbreviation 'D&R' is not expanded but is likely understood in context. It distinguishes from the sibling tool 'lc_get_dr_rule' which retrieves a single rule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'lc_get_dr_rule' or other list tools. There is no mention of prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only says 'List external adapter Hive records,' without stating that it is read-only, whether there are side effects, pagination, ordering, or any limitations. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it is under-specified and lacks critical information. Conciseness should not come at the expense of clarity; here it is too minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0% schema coverage, the description should provide substantial context. It fails to explain what a 'Hive record' is, how to interpret results, or any usage implications. The tool is complex (two parameters, one required) but the description is far too sparse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter descriptions are included. The tool description does not explain the meaning of 'oid' (required) or 'limit' (optional). 'oid' is ambiguous (could be organization ID or adapter ID). No additional semantic value added over the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'List external adapter Hive records,' indicating the action (List) and resource (external adapter Hive records). It clearly implies retrieval of multiple records, distinguishing from sibling tools like lc_get_external_adapter which likely retrieves a single record. However, 'Hive records' is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_get_external_adapter or lc_set_external_adapter. There is no mention of prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden, but it only states 'list' without disclosing pagination, default limit, return format, or read-only nature. This lack of behavioral detail forces reliance on implicit understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), but it lacks structure and essential details. While brevity is valued, it sacrifices clarity and completeness for the agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (list with two parameters) and lack of output schema, the description is incomplete. It fails to provide enough context for an agent to understand what the response contains or how to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter explanations. It does not clarify what 'oid' or 'limit' mean, leaving the agent to infer from names alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists false-positive rules for an org, with a specific verb and resource. However, it does not explicitly distinguish from sibling tools like lc_get_fp_rule, which might cause confusion for an agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., lc_get_fp_rule). It does not provide any context for appropriate usage, prerequisites, or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, placing full burden on description. The description only states the basic operation without disclosing behavioral aspects like pagination, default limit, or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but too terse for the tool's complexity. It could be expanded without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no behavioral context, the description is severely incomplete for effective tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, yet the description does not explain any parameter (e.g., oid, hive_name, limit, partition_key). It fails to add meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists records from a Hive partition, with a specific verb and resource. However, it does not differentiate from sibling tools like lc_get_hive_record or lc_list_hive_types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as pagination behavior, required permissions, or what constitutes 'metadata'. The word 'list' implies read-only, but no further details are given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is overly minimal and omits important details. It is front-loaded but lacks substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters and no output schema, the description is insufficient. It does not explain what 'ingestion key metadata' includes or how the 'limit' parameter affects results, making it incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the tool description does not explain the parameters 'oid' or 'limit'. It adds no meaning beyond the schema field names, failing to compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and resource 'ingestion key metadata' for an org, clearly stating the tool's purpose. It distinguishes from sibling list tools by the resource type, though 'metadata' is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lc_list_api_keys or lc_list_installation_keys. No context about prerequisites or use cases is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only says 'list records' without mentioning pagination, ordering, or scope. The limit parameter is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks substance. It could be expanded to include parameter context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and two parameters, the description is inadequate. It does not explain return values, pagination behavior, or how to use the limit parameter. Sibling tools with similar names are not differentiated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the meaning or usage of the two parameters (oid, limit). The description adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and resource 'organization-note Hive records', distinguishing it from get_org_note but not from list_hive_records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like list_hive_records or get_org_note. The description does not mention prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not state read-only nature, side effects, or any behavioral constraints beyond the verb 'List'. Lacks disclosure of important traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is very concise but underspecified. It is front-loaded but fails to convey essential details, making it minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Incomplete for a tool with two parameters and no output schema. Does not explain the role of 'oid', the meaning of 'playbook Hive records', or how this differs from similar list tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention 'oid' or 'limit' at all. No additional meaning is added beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Verb 'List' and resource 'playbook Hive records' are clear, but the phrase is ambiguous compared to siblings like 'lc_list_hive_records' or 'lc_get_playbook'. It does not differentiate from other list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No mention of prerequisites, pagination, or filtering. The required parameter 'oid' is not explained.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose whether the operation is read-only, requires authentication, or has any side effects. For a listing tool, it likely performs a read, but this is not stated. The description lacks behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. While it is front-loaded and to the point, it sacrifices important details. It could be expanded slightly to include parameter hints or usage context without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, no annotations, and parameters are undocumented, the description is insufficient for an agent to use the tool correctly. It does not explain return format, pagination, or error scenarios. Compared to sibling tools with more detailed descriptions, this is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the two parameters (oid and limit). Oid is likely an identifier for the query hive or organization, but no clarification is given. Limit defaults to 100, but its meaning is only implied. The description adds no value beyond the schema names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'saved LCQL queries' with the location 'query hive'. It distinguishes from siblings like lc_get_saved_query (which retrieves a single query) and lc_execute_saved_query (which executes one). However, it does not explicitly differentiate itself, but the purpose is specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_saved_query or lc_execute_saved_query. There is no mention of appropriate contexts, prerequisites, or when not to use it. The description solely states what it does without any usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden for behavioral disclosure. It only mentions 'bounded page' implying pagination, but does not explain default sorting (e.g., chronological), what happens when no events match, whether the result set is limited, or any side effects. The schema's cursor and is_forward parameters hint at pagination direction, but the description does not clarify.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no waste. It is appropriately concise for a simple function, but could have included more detail without becoming verbose. The structure is good, but the brevity comes at the cost of missing critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters (4 required), no annotations, and no output schema, the description is severely incomplete. It fails to explain pagination parameters (limit, cursor), filtering (event_type), time range (start, end), or direction (is_forward). An agent cannot reliably use this tool without guessing parameter formats and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to any of the 8 parameters. It does not explain that oid is likely the organization ID, sensor_id identifies the sensor, start and end are timestamps (epoch seconds), limit controls page size, cursor enables pagination, event_type filters, or is_forward controls time order. The agent must infer all parameter semantics from the schema alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List one bounded page of historical events for one sensor' which specifies the verb (list), resource (historical events), and scope (one sensor, one page). It is specific enough to distinguish from tools like lc_get_event (single event) or lc_get_sensor_event_overview (overview), though it does not explicitly name siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_get_event, lc_get_sensor_event_overview, or lc_list_child_events. There are no when-to-use or when-not-to-use hints, and no mention of prerequisites like authentication or sensor existence.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only implies a read operation ('List tags'). It does not disclose pagination, ordering, rate limits, or any side effects. For a list operation, this is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence, but it sacrifices necessary detail. It is front-loaded but incomplete. Every word earns its place, but additional context is missing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the two parameters (with required oid) and no output schema, the description is incomplete. It does not specify what data is returned, the format of tags, or the effect of the limit parameter. The tool could be used but with uncertainty.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the parameters (oid, limit). With 0% schema coverage, the description should compensate by describing what oid refers to (likely org ID) and how limit affects results. It adds no value beyond the schema's basic field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists tags observed across sensors in an org, which aligns with the tool name. However, it lacks specificity about what constitutes a 'tag' and how it differs from similar list tools like lc_list_sensor_tags, though it is generally clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as lc_list_sensor_tags or other list tools. There is no mention of prerequisites or exclusions, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral info. It does not disclose whether the operation is read-only, destructive, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (5 words) and front-loaded with the verb and resource. However, it lacks any additional structure or detail, making it minimally viable but not efficient in conveying necessary info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and simple inputs, the description does not explain the return value format or any other context. It leaves the agent guessing what 'user permission mappings' looks like in the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'oid' has no schema description (0% coverage) and the tool description does not explain its meaning or how to obtain it. The parameter is completely opaque.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('List') and resource ('user permission mappings for an org'). It distinguishes itself from siblings like lc_list_users and lc_explain_permission, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention any preconditions, when-not-to-use, or related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavioral traits like read-only nature, pagination (implied by cursor/limit params), authentication needs, or rate limits. Only states the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
At 5 words, it is very concise but lacks structure. It front-loads the purpose but omits necessary details. A good compromise would be slightly longer to cover key aspects.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (11 params, no output schema, no annotations), the description is severely incomplete. It does not explain how to use the tool, what the response contains, or how it differs from other vulnerability list tools. Highly incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and description adds no meaning for any of the 11 parameters. Does not explain what 'oid', 'cve', 'limit', 'cursor', etc. represent. Completely inadequate for a parameter-heavy tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List endpoints affected by one CVE' is specific about the verb and resource. It distinguishes from sibling tools that list CVEs themselves (lc_list_vulnerability_cves) or all endpoints (lc_list_vulnerability_endpoints), though it could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like lc_list_vulnerability_endpoints. No prerequisites or context about required parameters (oid, cve) are mentioned. Usage is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey behavioral traits. It does not mention read-only nature, pagination (cursor parameter), required permissions, or return structure. The description is too sparse to inform agent behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it is under-informative; conciseness should not come at the cost of missing essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high number of parameters (9), no output schema, and many sibling vulnerability list tools, the description is very incomplete. It does not explain pagination, filtering, sorting, or how the output relates to other vulnerability endpoints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no meaning to any of the 9 parameters. It fails to explain what 'oid' represents or how 'limit', 'filters', 'sort_by', etc., affect the results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (endpoints) with additional context (vulnerability counts). It conveys the core purpose but does not distinguish from sibling tools like lc_list_vulnerability_cve_hosts or lc_list_vulnerability_snapshots.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose side effects, authorization needs, rate limits, pagination behavior (though parameter 'cursor' suggests pagination), or response format. Minimal transparency beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (one sentence). However, given the tool's complexity (12 parameters), it could be slightly expanded without losing conciseness to improve usability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Incomplete for a tool with 12 parameters, no output schema, no parameter descriptions, and no behavioral guidance. Does not explain return values, pagination, or filtering. Requires additional documentation for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter explanations. It does not clarify what 'oid' or 'sensor_id' represent, nor how optional parameters like 'search', 'filters', 'sort_by' work. The description provides no value beyond the schema itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb (list), resource (vulnerable packages and CVEs), and scope (on one sensor). It distinguishes from sibling tools that operate on different scopes (e.g., CVEs across sensors or packages globally), but does not specify if it lists all packages or only those with vulnerabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives guidance. Among siblings, there are tools like lc_list_vulnerability_cve_hosts and lc_list_vulnerability_cve_packages, but the description does not differentiate when to use this tool versus those.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits. It does not mention if the operation is read-only, destructive, or requires authentication, leaving the agent without critical safety and usage context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise, but it lacks necessary detail and structure. It does not earn its place by providing sufficient information for proper tool use.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no param descriptions, no output schema, and many sibling tools, the description is extremely incomplete. It fails to define 'resolution overlays', explain parameters, or describe return values, making it inadequate for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any parameters. The agent cannot understand the meaning or purpose of 'oid', 'limit', 'scope', 'cursor', or 'resolutions' from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists 'stored vulnerability finding resolution overlays', indicating the verb (list) and resource (resolution overlays). It distinguishes from sibling list tools like lc_list_vulnerability_cves or lc_list_vulnerability_endpoints by focusing on resolutions, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not specify prerequisites, context, or when not to use it, making it unclear for an agent to select among many list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It states the tool lists rules but does not describe pagination, required permissions, or what the output represents. The 'limit' parameter's effect is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence but is too minimal for the tool's complexity. It could include more detail without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (list with two parameters), the description lacks essential context about pagination, required permissions, and the nature of YARA rules versus sources. It is insufficient for complete agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema parameter coverage is 0%; the description adds no information about 'oid' (required organization ID) or 'limit' (pagination). This leaves the agent without necessary context for correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('list') and the resource ('YARA scanning rules'), with the scope 'for an org'. This distinguishes it from other list tools in the sibling set, though it does not differentiate from lc_list_yara_sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_list_yara_sources or other list tools. No mention of prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present. The description implies a read operation by mentioning 'returning checkpoint state for resume', but does not disclose whether it mutates state, requires authentication, or has rate limits. The behavioral context is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise. However, it sacrifices clarity and completeness at the expense of brevity. It is front-loaded but lacks essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is incomplete for a tool with 4 parameters and no output schema. It does not explain the return value beyond 'checkpoint state', nor does it describe pagination behavior or the meaning of 'bounded'. Sibling tools exist for related search operations, but no differentiation is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters (oid, query_id, limit, token) with 0% description coverage. The description does not explain any parameter, leaving the agent to infer meaning from names alone. This is a significant gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool polls one bounded LCQL search page and returns checkpoint state for resume. It uses a specific verb 'poll' and identifies the resource as a search page. While jargon like 'LCQL' may assume domain knowledge, the purpose is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_execute_search_query or lc_cancel_search_query. The description does not mention prerequisites, context, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only says 'Preview linking telemetry to a case.' It does not disclose whether the action is read-only, what side effects occur, or any limitations. Behavioral traits are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), but it sacrifices necessary detail for complexity. It is front-loaded but insufficient for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given six parameters (including a nested object), no output schema, and no annotations, the description fails to provide essential information about the preview behavior, return values, or how to use the parameters. It is severely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no parameter explanations. It does not clarify the meaning of oid, event, note, verdict, case_number, or token_ttl_seconds. This is a significant gap given six parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Preview linking telemetry to a case.' The verb 'preview' and resource 'telemetry linking to a case' are specific. It distinguishes from siblings like lc_preview_add_case_artifact by focusing on telemetry. However, it does not provide deeper context on what linking telemetry means.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_preview_add_case_detection. No prerequisites, context, or conditions for use are mentioned. The description gives no decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits. The term 'Preview' suggests no side effects, but this is not explicitly stated. The agent cannot confirm whether this is a safe, read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is concise and front-loaded, but it is too minimal. While it avoids verbosity, it sacrifices necessary detail. It earns its place but could be improved with additional context without becoming lengthy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no output schema, no annotations), the description is incomplete. It does not explain what 'preview' entails, what the return value is, or any constraints (e.g., required permissions). An agent would need to infer much from the tool name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning beyond the parameter names. The three parameters (email, group_id, token_ttl_seconds) are not explained; the description only mentions 'user' and 'group' implicitly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Preview adding a user as a group member.' It specifies the resource (group) and the operation (preview add), distinguishing it from sibling tools like 'lc_preview_remove_group_member' and 'lc_add_group_member' (implied). However, it could more explicitly differentiate from similar preview actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives (e.g., actual add after preview), nor does it explain the purpose of previewing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description mentions 'preview' implying no actual side effect, but does not explicitly state that it is safe or read-only. With no annotations, the description fails to disclose behavioral traits like whether it modifies state or requires specific permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It could benefit from being slightly more detailed without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description fails to provide adequate context. It does not explain the return value, any prerequisites, or side effects, leaving the agent with insufficient information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 4 parameters (oid, email, permission, token_ttl_seconds) with 0% schema description coverage. The tool description does not explain what these parameters represent or how they should be used, leaving the agent without critical semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action: 'Preview granting one permission to a user.' It uses a specific verb and resource, and the naming convention differentiates it from sibling tools like lc_preview_remove_user_permission.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., lc_preview_set_user_role, lc_preview_invite_user). The description lacks context about prerequisites or appropriate conditions for previewing a permission grant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral information. It states the tool is a 'preview' operation, implying it is non-destructive, but does not explicitly confirm read-only behavior. There is no mention of authentication requirements, rate limits, or what the preview returns. The limitation 'up to 200 cases' is noted but not explained (e.g., what happens if more than 200 are provided). Critical behavioral traits are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 5 words, which is very concise. However, conciseness should not come at the expense of necessary information. The sentence is front-loaded with the action and limit, but it omits many details that could be added succinctly. It earns a 3 because it is minimal but not overly verbose; it could be improved without becoming too long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, no output schema, no annotations) and the large sibling set of preview tools, the description is insufficiently complete. It does not explain what the preview generates (e.g., a diff summary, a count of affected cases, or an error report). The relationship to other preview tools (e.g., lc_preview_update_case for single cases) is not addressed. Key aspects like how to interpret the result or what the 'token_ttl_seconds' parameter affects are missing, making the description inadequate for a tool with such rich input capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter descriptions exist in the schema. The tool description does not describe any of the 10 parameters (oid, case_numbers, tags, etc.) beyond what is implied by their names. For instance, 'case_numbers' could be list of case identifiers, but the description does not confirm format or requirements. The token_ttl_seconds parameter's purpose (probably related to an authorization token) is entirely unexplained. The description adds no value for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to preview a bulk update of up to 200 cases. The verb 'preview' and resource 'cases' are explicit, and the 'bulk-update' qualifier distinguishes it from singular update previewing (lc_preview_update_case). However, it does not distinguish itself from other bulk preview tools like lc_preview_add_case_tags, but that is partially acceptable given the naming convention.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of related tools like lc_confirm_action for committing the update, or lc_update_case for direct execution. The description does not indicate whether it should be used only before a subsequent commit action, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden of disclosure. It only says 'preview' without explaining whether it validates parameters, simulates creation, or has side effects. Behavioral traits are almost absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence, but it sacrifices completeness. It is not verbose, but it lacks critical details, making it less useful than it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and 0% schema coverage, the description should provide more context. It does not explain return values or the effect of the preview, leaving the agent undersupported.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any parameter meanings. The agent must infer from names alone, which is insufficient for a tool with 5 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview) and the resource (creating an API key), distinguishing it from other preview tools. However, it does not explain what 'preview' entails, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as other preview tools or actual creation. The description provides no context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. 'Preview' implies a non-destructive simulation, but no details on side effects, permission requirements, or what the preview actually validates. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at seven words, fitting on one line. While efficient, it sacrifices necessary detail for brevity. Still, it is not verbose or poorly structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain the preview behavior, return value, or parameter purposes, leaving the agent without critical context for correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 5 parameters (1 required) with 0% description coverage, and the tool description provides no parameter-level guidance. The agent has no context on what each parameter does, severely hampering correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Preview creating') and the resource ('LimaCharlie case'), distinguishing it from other actions. However, it lacks specificity on what 'preview' entails, such as validation or cost estimation, which could aid differentiation from the many sibling preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like lc_preview_update_case or actual case creation. The description does not mention context, prerequisites, or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. 'Preview' implies no side effects, but it fails to explain what the preview does (e.g., validate, simulate costs, etc.) or what the response contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (four words) and to the point. While concise, it could be expanded to include critical information without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is completely inadequate for a tool with three parameters (one required, nested object), no output schema, and no annotations. It fails to explain what the preview returns, how to use parameters, or any behavioral details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no information about the three parameters (extension_name, token_ttl_seconds, extension_definition). Schema coverage is 0%, so the description does not compensate, leaving parameter meanings entirely unspecified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview creating an extension definition' clearly indicates the tool is for previewing, not actually creating, an extension definition. It uses a specific verb and resource, but does not differentiate from sibling preview tools like 'lc_preview_update_extension'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus other preview or creation tools, nor does it mention any prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states 'Preview creating a new organization' but does not specify whether this operation has side effects, what it validates, or what the output contains. The term 'Preview' implies no permanent change, but this is not made explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but potentially too sparse. It lacks structure and front-loads only the basic purpose. While no unnecessary words exist, the brevity sacrifices valuable information that could aid the agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, numerous sibling preview tools), the description is incomplete. It does not clarify what the preview returns, how it differs from actual creation, or any constraints. The agent would need additional context to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters with 0% description coverage, yet the description adds no explanation for any parameter (name, location, template, token_ttl_seconds). The agent receives no semantic help beyond parameter names and types, which is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Preview) and the resource (creating a new organization), distinguishing it from sibling preview tools for other resources. However, it does not elaborate on what the preview entails, which may leave some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_create_org or lc_check_org_name). The description does not indicate prerequisites, conditions, or when not to use it, leaving the agent to infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Preview deleting' implying a non-destructive operation, but it does not explicitly confirm that no actual deletion occurs. The phrase 'through the partial-merge hook' is vague and adds no clarity about side effects or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 12-word sentence, which is brief. However, it lacks structure and fails to provide essential details, trading completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given five parameters, no output schema, and a network of sibling preview tools, the description is far from complete. It does not explain what a preview entails, what the partial-merge hook means, or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must explain parameters. It only mentions 'ai_memory entry' but does not describe oid, agent, memory_name, partition_key, or token_ttl_seconds, leaving their purpose undefined.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The verb 'Preview deleting' clearly indicates the action, and 'one ai_memory entry' specifies the resource. However, it does not differentiate from sibling lc_preview_delete_ai_memory_record, which also involves deletion preview but for a different entity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool compared to alternatives like the actual delete tool or other preview tools. There is no mention of context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description simply says 'Preview deleting', which hints at a non-destructive dry-run but does not explicitly state that no changes occur. It fails to disclose operational details like permissions required, idempotency, or what the preview returns (no output schema). The behavior is largely implicit from the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but too minimal. It lacks structure and additional details that could be included without making it verbose. It is front-loaded with the verb but sacrifices informativeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the many sibling tools and the absence of an output schema, the description is severely incomplete. It does not specify what the preview returns, how it differs from similar preview operations, or what the user should expect. The agent lacks sufficient context to use the tool correctly without relying on external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds nothing about the parameters. While 'oid' and 'name' are somewhat self-explanatory, 'token_ttl_seconds' is not explained at all. The description does not compensate for the lack of schema descriptions, leaving parameter purpose ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting an AI skill Hive record' clearly specifies the action (preview deletion) and the target resource (AI skill Hive record). It distinguishes from sibling tools like lc_preview_delete_ai_agent and lc_preview_set_ai_skill by pointing to a different resource and operation. However, it does not explain what a 'Hive record' is, slightly reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other preview delete tools (e.g., lc_preview_delete_hive_record) or non-preview alternatives. There is no mention of prerequisites, such as needing the OID from a prior list/get operation, or that this is a dry-run before actual deletion. The agent receives no contextual cues for proper selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden of behavioral disclosure. It says 'Preview deleting,' which implies a non-destructive operation, but it does not explain what the preview returns, whether any state changes occur, or how the result should be used. This lack of detail is a significant gap for a preview action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but fails to convey necessary information. It is not verbose, but it sacrifices clarity for brevity. The structure is flat, with no front-loading of critical details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters, no output schema, and a complex sibling set, the description is too sparse. It does not explain what the preview produces, how to proceed after previewing, or how this tool relates to others like lc_confirm_action. The agent lacks sufficient context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description provides no explanation for any of the three parameters (oid, name, token_ttl_seconds). Despite the low coverage, the description adds no value beyond the tool's purpose. The agent cannot infer parameter meanings or constraints from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Preview deleting a cloud adapter Hive record,' which identifies a specific verb-resource combination and distinguishes from siblings like lc_preview_delete_hive_record (general) and lc_preview_set_cloud_adapter (different action). However, 'preview' is ambiguous—it could mean a dry-run or simulation, but the intent is reasonably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools include lc_preview_delete_hive_record for general hive records and lc_confirm_action for actual deletion, but the description does not differentiate contexts or state prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations describing safety or effects, the description carries the full burden. It states 'Preview deleting' which implies no destructive action, but it does not explicitly confirm that no changes occur, nor does it describe the output or return format. The behavioral disclosure is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but at the expense of completeness. It front-loads the key action but omits necessary details, making it under-specified rather than appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, zero parameter descriptions, and the presence of many similar sibling tools, the description fails to provide adequate context. An agent would not know what the preview returns, how to interpret it, or how this tool relates to others.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema lists 4 parameters (oid, name, namespace, token_ttl_seconds) with 0% schema description coverage. The description adds no information about what these parameters mean, how they affect the preview, or their expected values. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting a D&R rule' clearly states the verb ('preview deleting') and resource ('D&R rule'). It distinguishes among sibling preview_delete_* tools by specifying the resource type, though it could be more explicit about the 'preview' aspect (e.g., simulation vs. actual deletion).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_dr_rule, lc_list_dr_rules, or lc_set_dr_rule. There is no mention of prerequisites, sequence, or comparison to a non-preview delete tool (which may or may not exist).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states the action without revealing key traits: that it does not actually delete, what side effects (if any) occur, whether a token is generated for confirmation, or any required permissions. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, which is structurally efficient. However, it sacrifices necessary detail, making it under-specified rather than appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 'preview delete' action with three parameters and no output schema or annotations, the description is severely incomplete. It lacks information about operation semantics, parameter roles, and expected next steps (e.g., using lc_confirm_action), making it difficult for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no explanation for any of the three parameters (oid, name, token_ttl_seconds). The agent has no semantic understanding of these fields, hampering correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview deleting') and the resource ('an exfil event rule'), distinguishing it from sibling tools that deal with other entities. However, it does not clarify what 'preview' means operationally (e.g., simulation, permission check, impact analysis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_preview_delete_exfil_watch or lc_confirm_action. There is no indication of prerequisites, post-preview steps, or exclusion cases, leaving the agent without decision context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It says 'Preview deleting' but does not explicitly state that it is a dry run or what side effects occur. There is no mention of the output, return format, or any behavioral traits beyond the vague verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief (one sentence) but fails to convey necessary information. Conciseness should not come at the expense of clarity; here, the brevity makes the description inadequate for an AI agent to understand usage properly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and 0% schema description coverage, the description is completely inadequate. It does not explain the purpose of the preview, the expected outcome, or how parameters relate to the operation. The tool definition leaves too much ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not add any meaning for the three parameters (oid, name, token_ttl_seconds). The parameter names are somewhat self-explanatory but lack context such as data types, formats, or examples, which is critical for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Preview deleting') and resource ('exfil watch rule'), making it clear what the tool does. However, it does not clarify what 'Preview' means (e.g., dry run vs. actual deletion), and sibling tools like lc_preview_create_exfil_watch suggest a pattern but the distinction from a potential actual delete tool is not stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, expected inputs, or scenarios where this tool is appropriate. Sibling tools include many preview_delete_* tools but no explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present. The description only says 'preview deleting' without elaborating what a preview entails, any safety considerations, or return behavior. It fails to disclose that this is a dry-run and not an actual deletion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it is too brief and does not provide essential context. While efficient, it lacks substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and minimal annotations, the description should explain the preview behavior, output format, and any side effects. It fails to do so, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% per context signals, meaning the description adds no information about the two parameters (extension_name, token_ttl_seconds). The description does not compensate for this lack.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action 'preview deleting' and the resource 'extension definition', which is clear. However, among many sibling preview_delete tools, it does not differentiate itself beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., other preview delete tools or actual deletion tools). No prerequisites or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must carry behavioral disclosure. The word 'Preview' implies a dry run, but the description does not confirm that no changes occur, what the output contains, or any side effects. Minimal transparency beyond the action type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence) and front-loaded with purpose. However, it is too terse to be effective; every sentence should earn its place, but this one fails to provide necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has low complexity (2 params, no output schema), but the description does not explain what 'preview' entails, what the output will be, or how to interpret results. For a preview action, the expected output is critical context, and its absence makes the description incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the two parameters. 'group_id' and 'token_ttl_seconds' are not explained. The description repeats the tool name without elaborating on what each parameter does or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool previews deleting an organization group. It uses a specific verb 'Preview deleting' and identifies the resource 'organization group'. It distinguishes from other preview tools by specifying 'group', but not from sibling tools like lc_delete_group (not listed) or other preview_delete_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of when to preview versus actually deleting, or comparison with other preview or delete tools. The agent is left to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only says 'Preview deleting' but does not disclose what preview entails (e.g., dry run, token generation), auth requirements, or side effects. This leaves agents without critical behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence is concise but omits essential details. While there is no fluff, the brevity sacrifices necessary context for agent decision-making.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain the preview workflow, return value, or how results feed into subsequent actions (e.g., lc_confirm_action).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the tool description provides no parameter explanations. Critical fields like oid, hive_name, key, partition_key, and token_ttl_seconds are undefined, forcing agents to guess meaning from names only.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting a generic Hive record' clearly states the verb 'preview' and resource 'Hive record', distinguishing it from sibling tools like lc_get_hive_record (retrieval) and lc_preview_set_hive_record (modification). However, 'generic' and 'preview' lack specificity about scope or behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., actual deletion tool or other preview actions). No mention of prerequisites or subsequent confirmation steps (e.g., lc_confirm_action).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a dry-run operation but does not explain what the preview entails (e.g., what is returned, if any side effects, required permissions). With no annotations, more behavioral context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, but given the need to document three parameters and behavioral context, it is overly brief. It sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, no annotations, and three parameters. The description does not cover return values, preconditions, or what 'preview' means, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description provides no information about the three parameters (oid, name, token_ttl_seconds). The agent receives no guidance on what values to supply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('Preview deleting') and the resource ('logging collection rule'), distinguishing it from related siblings like lc_set_logging_rule and lc_list_logging_rules.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as when to preview before actual deletion. No contrast with similar preview tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It only states 'Preview deleting', but does not explain the preview mechanism, whether it returns a token for confirmation, or if it is idempotent. The token_ttl_seconds parameter hints at a token-based flow, but this is not connected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence), but it is overly minimal and lacks structure. It does not front-load key information such as the token-based confirmation flow. Some expansion would improve usability without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (preview delete with token), lack of output schema, and no annotations, the description is woefully incomplete. It fails to explain the preview lifecycle, how to interpret results, or how to proceed after preview.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate. It does not explain what 'oid' and 'name' represent (likely identifiers of the lookup record) or the purpose of 'token_ttl_seconds'. Parameters are essentially undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for previewing deletion of a lookup Hive record. It specifies the verb 'preview deleting' and the resource 'lookup Hive record', distinguishing it from sibling tools like lc_preview_delete_hive_record. However, it does not elaborate on what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_preview_delete_hive_record or actual deletion tools). There is no mention of prerequisites or context for using this preview functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The term 'preview' implies a dry-run operation, but the description does not disclose what happens during the preview, such as whether it returns an estimated impact, requires confirmation, or has any side effects. With no annotations, the description carries the full burden, and it is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks necessary detail. It is not overly verbose, but the brevity comes at the cost of informativeness; a longer description with key points would be more effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (many sibling preview tools, no output schema, no annotations), the description is inadequate. It fails to explain the preview behavior, return value, or how it fits with related tools like lc_get_org_note or lc_set_org_note.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 3 parameters with 0% description coverage. The description does not explain the meaning or role of 'oid', 'name', or 'token_ttl_seconds'. The agent cannot infer what values to provide or why token_ttl_seconds is needed, leaving a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview deleting') and the resource ('organization-note Hive record'), making the tool's purpose understandable. It is specific enough to differentiate from other tools that delete different resources, though it does not explicitly distinguish from sibling preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_preview_delete_hive_record or lc_preview_delete_org. There is no context about prerequisites, suitable scenarios, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. 'Preview' suggests no side effects, but this is not stated, nor does it mention idempotency, authentication needs, or output format. The description is insufficient for an agent to understand the tool's behavior beyond being a preview.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words), but this brevity sacrifices clarity and completeness. It is front-loaded with the core action, but the lack of detail makes it less useful than a slightly longer description that adds critical context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no output schema, and 0% parameter description coverage, the description should compensate. It fails to explain the return value, parameter meanings, or when to use it among many similar preview delete tools. The description is completely inadequate for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no explanation for the three parameters (oid, name, token_ttl_seconds). The agent cannot infer what values to provide for 'oid' and 'name' (likely playbook identifiers) or how 'token_ttl_seconds' affects the operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'preview deleting' and the resource 'a playbook Hive record'. It distinguishes from other preview delete tools by specifying the record type, and from non-preview tools by the 'preview' prefix. However, it does not explain what the preview entails (e.g., checks constraints or shows impact), leaving minor ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool rather than alternatives like lc_delete_playbook or other preview delete tools. The 'preview' prefix implies it's a safe check before deletion, but this is not explicit, and no alternatives or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a preview action (no actual cancellation) but does not disclose any additional behavioral traits like side effects, required permissions, or what 'preview' entails. With no annotations, the description carries full burden but provides minimal information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence with no fluff. However, it may be overly brief given the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks essential context: no explanation of input parameters, no output schema details, and no mention of behavior beyond 'preview cancelling'. The tool is incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameter descriptions are provided in the description or schema (0% coverage). The agent cannot determine the meaning or purpose of oid, task_id, selector, sensor_id, or token_ttl_seconds from the given text.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool previews the cancellation of a pending reliable task. It uses a specific verb and resource, distinguishing it from actual deletion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as the actual delete action or other preview tools. The description lacks context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states 'preview deleting' but does not clarify that no actual deletion occurs, or what the preview returns. The behavioral implications are opaque, which could mislead an agent into thinking the tool performs the deletion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one short sentence), but it omits critical information. It is front-loaded but under-specified, making it minimally acceptable for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is incomplete. It does not explain what the preview output is, how to interpret it, or how this tool fits into a larger workflow (e.g., followed by a confirm/delete step).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no parameter descriptions), and the description adds no information about the three parameters (oid, name, token_ttl_seconds). The agent receives no guidance on parameter purposes or formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting a YARA source.' clearly states the action (preview deleting) and the resource (YARA source). It distinguishes from sibling tools like lc_list_yara_sources and lc_preview_delete_yara_rule by specifying the resource type, but does not elaborate on what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this preview tool versus the actual delete operation (if one exists) or any alternatives. An agent has no context on workflow or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must inform about behavior. It says 'Preview sending', which ambiguously suggests a simulation, but does not confirm whether it actually sends or just shows a preview, nor disclose side effects, auth requirements, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-specified for a tool with 10 parameters. It could be more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 parameters, zero annotations, no output schema, and no schema descriptions, the description is severely inadequate. It fails to describe what the tool returns, parameter purposes, or usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate. The description does not explain any of the 10 parameters (oid, channel, question, feedback_destination, etc.), leaving their semantics entirely implicit from parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Preview sending' and the resource 'external acknowledgement request through ext-feedback', distinguishing it from sibling preview_feedback tools like lc_preview_feedback_question and lc_preview_feedback_simple_approval. It could be more explicit about what 'acknowledgement' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Among siblings are other preview_feedback tools, but the description never explains when to choose acknowledgement over question or simple_approval.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits beyond 'Preview merging'. It doesn't state whether the tool is read-only, requires specific permissions, or has any side effects. The description is insufficient for understanding safety and behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it lacks structure such as front-loaded key information or enumerated details. While brief, it does not fully earn its place as it omits critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of merging multiple source cases into a target, the description is very incomplete. No output schema is provided, and the expected return value (preview details) is not described. The agent would have to guess tool behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no information about the parameters (oid, token_ttl_seconds, target_case_number, source_case_numbers). The agent has no guidance on how to use these parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview merging') and the objects ('source cases into a target case'). It is specific and distinguishes this tool from siblings like lc_preview_update_case or lc_preview_bulk_update_cases, though it could elaborate on what 'preview' means in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lc_confirm_action for actual merge). There is no context about prerequisites or scenarios where preview is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only says 'without uploading bytes', implying no side effects, but fails to disclose auth requirements, rate limits, or what the preview returns. Insufficient for safe decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, very concise, but lacks structure and important details. Conciseness is good, but under-specification harms utility.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and 0% schema coverage, description is severely incomplete. Does not cover return value, side effects, parameter meanings, or prerequisites. Inadequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning description must compensate for three parameters (oid, name, token_ttl_seconds). Description provides no explanation of these parameters whatsoever, leaving the agent to guess their meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it previews a signed payload upload URL without uploading bytes. Verb 'Preview' and resource 'signed payload upload URL' are specific. Differentiates from actual upload tools by explicitly saying 'without uploading bytes', but doesn't distinguish from other preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_get_payload_download_url or actual upload tools. No explicit context or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits. It states 'Preview' but doesn't clarify if it's safe, non-destructive, or what the preview entails, leaving ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) and front-loaded. However, it is too brief, lacking necessary details; while efficient, it under-delivers for the required information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, and the presence of many sibling preview tools, the description is incomplete. It does not explain the return value or workflow context needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no parameter information. The agent must infer parameter meanings from names alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool previews removing network isolation from one sensor, specifying the action and resource. However, it does not differentiate among sibling preview tools, though the name 'rejoin_sensor' is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like executing the actual rejoin or other preview actions. The description implies a preview but lacks context on prerequisites or whether confirmation is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description only says 'Preview rotating', which implies a dry-run, but it does not explicitly state whether the operation is read-only or has side effects. The parameter token_ttl_seconds suggests configuration, but no behavior is disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, no wasted words, but it lacks structure or additional context. It is concise but could benefit from slightly more detail without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotations, and 0% parameter coverage, the description is severely incomplete. It does not explain what the preview returns, prerequisites, or how to use the parameters, leaving an AI agent with insufficient information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no explanation for any of the three parameters (oid, extension_name, token_ttl_seconds). The meaning of oid and the purpose of token_ttl_seconds are entirely unspecified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview rotating an extension subscription API key' clearly defines the action (preview rotate) and resource (extension subscription API key), distinguishing it from sibling preview tools like lc_preview_subscribe_extension or lc_preview_update_extension.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as lc_preview_update_extension or lc_preview_subscribe_extension. No prerequisites or context are provided, making it unclear if certain conditions must be met.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It implies a read-only preview but does not explicitly confirm safety, side effects, authentication needs, or other behavioral aspects. Very minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks essential content. Conciseness is not a substitute for missing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no output schema, no annotations), the description is grossly incomplete. It fails to provide parameter semantics, behavioral details, or usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage for its 7 parameters. The description does not explain any parameter, leaving the agent with no guidance on what 'oid', 'task', 'context', etc., represent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'preview queueing' and the resource 'one reliable task', making the purpose clear. However, with many sibling preview tools, it does not explicitly distinguish itself beyond mentioning 'reliable task', which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_preview_delete_reliable_task or other preview tools. The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavioral traits. It only hints at non-destructive nature ('preview') but doesn't confirm what the preview returns, whether it mutates state, or any constraints. No mention of authorization or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (6 words), but this comes at the cost of missing essential details. It is front-loaded but lacks structure; a single sentence is not well-structured for complex tools.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and many similar preview tools, the description is incomplete. It does not explain the return value, how the preview works, or differentiate from sibling previews.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, putting full burden on the description. The description does not explain any of the 4 parameters (oid, entity_id, case_number, token_ttl_seconds). Parameter names alone are insufficient to convey meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('preview removing') and resource ('entity from a case'). It distinguishes from siblings like 'lc_preview_remove_case_artifact' or 'lc_preview_add_case_entity' by specifying the entity removal context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus its siblings (e.g., actual removal vs preview, or other preview removals). No context about typical scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. 'Preview' suggests a dry run, but the description does not confirm whether it actually performs the removal or just shows the impact. No details on side effects or authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks necessary detail. It front-loads the main action but sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is woefully incomplete. It fails to explain what 'preview' means, what the tool returns, or how to use the parameters. A minimal description for a tool of this complexity should provide parameter context and expected output behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 4 parameters (oid, case_number, telemetry_id, token_ttl_seconds). The agent cannot infer their purpose or format from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview removing telemetry') and the resource ('a case'), matching the tool name. However, it does not distinguish this from sibling tools like lc_preview_add_case_telemetry or lc_preview_update_case_telemetry, missing an opportunity to specify the removal aspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context for telemetry removal, or distinction between preview and actual removal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist. The description only says 'Preview removing,' implying a dry-run, but does not disclose side effects, authorization requirements, or the nature of the preview (e.g., what is returned). Minimal behavioral information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (one sentence), but at the cost of omitting critical details. While front-loaded, it sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and three undocumented parameters, the description fails to provide sufficient context for an AI agent to invoke this tool correctly. It does not explain return values, parameter use, or the preview mechanism.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain any of the three parameters (group_id, member_oid, token_ttl_seconds), leaving their purpose unclear beyond the schema's field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Preview removing an organization from a group,' specifying the verb and resource. It distinguishes itself from sibling tools like lc_preview_add_group_org by focusing on removal. However, it lacks explanation of what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_confirm_action or lc_cancel_action. The description does not provide context for invocation or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies 'preview' but does not explain what that entails (e.g., no changes are made, what is returned). No annotations to fill the gap. Missing details about side effects, permissions, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence, 7 words). While not verbose, it lacks structure and fails to include essential information such as parameter details or usage context. It is an example of under-specification rather than efficient brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of schema descriptions, annotations, and output schema, the description provides almost no context. It does not cover the preview's behavior, return value, or parameter meanings, leaving significant gaps for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fails to explain any parameters. It does not mention that email and group_id are required, nor what token_ttl_seconds controls. Users must infer from names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview removing) and the resource (a user from group owners). It distinguishes from siblings like lc_preview_add_group_owner or lc_preview_remove_group_member, but could be more explicit about the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus similar preview tools or the actual remove action. No prerequisites or context for when this preview is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only states 'Preview revoking one permission.' It does not disclose what happens after the preview (e.g., need to confirm), any side effects, or authentication requirements. The behavioral implications are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action. It is concise, but this conciseness sacrifices completeness. The structure is minimal yet efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters, no output schema, no annotations), the description is severely incomplete. It fails to explain the preview workflow, parameter purposes, or return value. For a tool with many siblings, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It fails to explain any of the 4 parameters (oid, email, permission, token_ttl_seconds). The phrase 'one permission from a user' vaguely maps to email and permission but adds no detail about the parameters' roles or formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview revoking one permission from a user' is specific with a verb and resource, and distinguishes from sibling tools like lc_preview_add_user_permission and lc_list_user_permissions. However, it does not clarify what 'preview' entails, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_preview_add_user_permission, lc_list_user_permissions, or lc_explain_permission. The description lacks context on when to preview a removal vs. actually removing or listing permissions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It says 'Preview', implying a read-only operation, but does not confirm that no changes are made, nor does it describe what happens during preview (e.g., validation, simulation). The term 'non-impersonated' hints at using the current user's identity but lacks clarity. The description omits critical behavioral details such as side effects or return value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise and front-loaded. However, it is too minimal—it does not earn its place by providing sufficient information. While not verbose, it sacrifices clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (5 parameters, nested object, many sibling preview tools, no output schema), the description is severely incomplete. It fails to explain what a 'service request' entails, how to use 'request_data', or what the preview result contains. The tool cannot be correctly invoked based solely on this description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description adds no context about any of the 5 parameters, including the required 'request_data' (object with additionalProperties) and 'service_name'. Without parameter explanations, an agent cannot correctly populate fields. The description fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview a generic non-impersonated service request' clearly identifies the verb (Preview) and resource (service request), and specifies 'generic' and 'non-impersonated' to narrow the scope. However, it does not distinguish this tool from the many other lc_preview_* tools, such as lc_preview_add_case_artifact or lc_preview_create_case, which are more specific. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or context. For example, it does not state that this tool should be used for service requests not covered by other preview tools, nor does it explain what 'non-impersonated' means in practice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Preview', which suggests no side effects, but it does not disclose what the preview returns (e.g., validation errors, estimated effects), required permissions, or whether it is safe (read-only). This is insufficient for a tool with 10 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but at the expense of completeness. Given the tool's complexity (10 parameters, nested objects), a slightly longer description would be justified. It is front-loaded with the key verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters, 3 required, a complex 'data' object, no output schema, and no annotations, the description is critically incomplete. It does not explain the preview behavior, parameter usage, return format, or any constraints. This is far from adequate for an AI agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 10 parameters with 0% schema description coverage. The description provides no explanations for any parameter, such as the 'data' object structure, the meaning of 'ui_actions', or the role of 'oid'. This places a heavy burden on the description, which it fails to meet.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'Preview creating or updating' and the resource 'AI agent Hive record', which is clear. It distinguishes from siblings that operate on different entities (e.g., lc_preview_set_hive_record) or other actions (e.g., lc_preview_delete_ai_agent). However, it does not explain what 'preview' entails, which could be inferred from the naming but is not explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool is used to preview changes before applying them, but it does not specify when to use it versus alternatives like lc_confirm_action or non-preview versions. No exclusions or alternative tool mentions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. 'Preview' suggests a dry-run, but the description does not confirm that no action is taken, nor does it mention permissions, side effects, or response structure. Insufficient for safe agent invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks necessary detail. It is front-loaded with the core action, but the brevity sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters including nested objects, no output schema, no annotations), the description is critically incomplete. It fails to explain the preview semantics, parameter roles, or expected outcomes, leaving the agent without adequate context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no explanation for any of the 10 parameters. Parameters like 'data' (nested object), 'etag', 'tags', etc., are left entirely undefined. The agent cannot infer how to set them correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it previews creating or updating an AI skill Hive record, using a specific verb ('Preview') and resource ('AI skill Hive record'). It distinguishes from sibling tools that modify related entities (e.g., enabling/disabling skills, deleting skills). However, it could be more explicit about the difference from a hypothetical non-preview version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives (e.g., actual creation via other endpoints, preview for other resources). Missing context about prerequisites or conditions for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'preview' but does not disclose that it likely performs a dry-run without side effects. There are no annotations to provide safety hints. The description does not clarify whether it modifies state or what the return value represents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. While it is front-loaded, it sacrifices necessary clarity and parameter explanation. It could be expanded without becoming bloated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four parameters, no output schema, and a minimal description. Given the complexity and lack of annotations, the description is insufficient. It does not explain what a preview entails, what the parameters do, or what the expected result is.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage for parameters. The description does not explain any parameter names (oid, name, enabled, token_ttl_seconds) or how they map to the 'cloud adapter Hive record' and 'enabled metadata'. The agent cannot determine what values to supply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a preview action for toggling the enabled metadata of a cloud adapter Hive record. It distinguishes from generic sibling tools like lc_preview_set_hive_record_enabled by specifying the resource type. However, it does not define the term 'preview' further.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_preview_set_cloud_adapter or lc_set_cloud_adapter. The term 'preview' implies testing but is not explained. No when-not-to-use or prerequisite information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It states 'Preview', implying a non-destructive, read-only operation, but does not confirm idempotency, side effects, or authorization needs. The return value is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence, but it lacks structural elements like parameter highlights or usage examples. While not verbose, it is under-specified and does not earn its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain how parameters affect the preview, what the user should expect, or any constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about the three parameters. It does not explain what the permissions array should contain, the format of group_id, or the purpose of token_ttl_seconds.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Preview' and resource 'replacing a group's permission list', clearly indicating the tool's function. It differentiates from other preview tools by specifying 'replacing a group's permission list', though it doesn't elaborate on the preview output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It implies a dry-run before a potential commit action (e.g., lc_confirm_action), but this is not stated. No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description notes that this is a 'preview' operation and that it preserves existing metadata, which gives some behavioral insight. However, there are no annotations to supplement this, so the description must carry the full burden. It fails to disclose whether this tool is read-only, what permissions are required, or what happens after the preview (e.g., does it return a change set?).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded with the key action. It avoids unnecessary words. However, it could be improved by adding structure such as separate sections for behavior or parameter hints, but the brevity is not a significant flaw.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 6 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain what the tool returns, side effects, or prerequisites. It provides only the most basic action without any context that would help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 6 parameters with 0% description coverage, yet the description adds no parameter-level information. It mentions 'enabled metadata' but does not explain how the 'enabled' boolean parameter works, nor does it clarify the roles of 'oid', 'hive_name', 'key', 'partition_key', or 'token_ttl_seconds'. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that this tool previews setting a Hive record's enabled metadata while preserving existing metadata. Although it does not explicitly differentiate from siblings like 'lc_preview_set_hive_record', the name and description together imply the specific focus on the 'enabled' field, making the purpose relatively clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the many similar sibling tools (e.g., lc_preview_set_hive_record, lc_set_hive_record_enabled). The description does not mention prerequisites, typical use cases, or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It states 'preview' implying no side effects, but fails to clarify if the operation is dry-run, what is returned, or any other behavioral details. Insufficient for an agent to understand side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure such as bullet points or emphasis. It is not wasteful but could be more informative within the same length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no output schema), the description is severely incomplete. An agent cannot understand required inputs or expected outputs without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 8 parameters with no descriptions, and the tool description does not explain any parameters. With 0% schema description coverage, the agent has no insight into parameter meaning beyond names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as previewing creation or update of a logging collection rule. It distinguishes from siblings like lc_preview_delete_logging_rule. However, 'preview' is somewhat vague without further context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_list_logging_rules or lc_preview_set_* siblings. There are no prerequisites or context cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It states 'Preview creating or updating' but does not explicitly state that it has no side effects (e.g., it does not commit changes), nor does it mention authentication requirements, rate limits, or return format. The term 'preview' implies a dry-run, but this is not confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but too brief to convey necessary information. It lacks structure and front-loads the key action, but the minimalism sacrifices clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, 0% schema coverage, no output schema, no annotations), the description is severely incomplete. An AI agent would have insufficient context to understand what data to provide or what the preview returns. Sibling tools like lc_preview_set_hive_record or lc_set_playbook might offer more clues, but the description itself fails to provide adequate completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema has no descriptions for any of the 10 parameters (oid, name, data, etag, tags, expiry, comment, enabled, ui_actions, token_ttl_seconds). The description adds no explanation of what these parameters mean, how to use them, or their expected formats. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Preview' and the resource 'creating or updating a playbook Hive record,' which aligns with the tool's name and distinguishes it from other playbook tools like lc_get_playbook or lc_preview_set_playbook_enabled. However, it does not elaborate on the exact semantics of 'preview' (e.g., validation, simulated change, return expected result without commit), which could cause ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as lc_set_playbook (which presumably actually creates/updates) or other preview tools. There is no mention of use cases, prerequisites, or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must bear full weight. It only states 'Preview toggling' but does not explain what 'preview' entails—whether it is idempotent, what permissions are required, or what the outcome is. This under-disclosure is risky for a mutation preview tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (11 words), which is concise, but it sacrifices necessary detail. It front-loads the action and resource but leaves out critical information about the tool's behavior and parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a preview tool for a potentially risky action (toggling enabled state), the description is incomplete. It lacks explanation of the preview scope, return value (no output schema), and prerequisites. The description does not compensate for the absent annotations or schema details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description adds no meaning to the parameters (oid, name, enabled, token_ttl_seconds). Without any explanation, the agent cannot infer what values to provide for oid and name, or how enabled toggling works with them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it previews toggling the enabled metadata of a playbook Hive record, which is specific and distinguishes it from sibling tools like lc_preview_set_playbook or lc_set_playbook. The verb 'Preview toggling' is specific, but the phrasing could be more precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when to preview versus directly set enabled state, or what prerequisites are needed. Among many similar preview actions, the description lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description says 'Preview' but doesn't explicitly state that no persistent changes are made. With no annotations, the agent must guess if this is a dry run. It also doesn't describe what the preview returns (e.g., validation errors, match counts). Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (single sentence) but too terse. It lacks structure (e.g., listing key parameters or behavior). It could be improved with a brief addition about the preview's purpose without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 9 parameters, no output schema, and no annotations, the description is highly incomplete. It doesn't explain the preview's outcome or how parameters are used. Agents cannot reliably use this tool based solely on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description provides no parameter explanations. The 9 parameters (oid, name, query, etc.) are left completely undefined. The description adds zero value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Preview' and the resource 'saved LCQL query' with actions creating or updating. It differentiates from siblings like get/execute/delete by being a preview. However, it doesn't explicitly say 'simulate without saving' which would strengthen clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention 'use this to validate before executing' or contrast with lc_execute_saved_query or lc_get_saved_query. Agents are left to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states 'Preview toggling', implying a dry-run, but does not disclose behavioral traits such as side effects (should be none), error conditions, authentication needs, or rate limits. With no annotations, the description carries full burden but is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: a single sentence with no fluff. However, it sacrifices substance for brevity. It earns its place but could include more information without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, 0% schema coverage, no output schema, and no annotations, the description is severely incomplete. It does not explain what the preview returns, how to interpret results, or how parameters relate to the operation. The agent lacks critical information to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description does not explain any parameter semantics. For example, it doesn't clarify what 'oid' vs 'name' identify for the secret, or the role of 'token_ttl_seconds'. The description adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool previews toggling a secret Hive record's enabled metadata. The verb 'preview toggling' indicates it's a dry-run operation, and 'secret Hive record's enabled metadata' specifies the resource. It distinguishes from sibling tools like lc_preview_set_secret (which likely sets the secret) and lc_preview_set_hive_record_enabled (for general Hive records), but the phrasing 'preview toggling' could be clearer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites, context, or when not to use it. The sibling set includes many preview_set_* tools without differentiation, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description bears full burden. It does not disclose what 'preview' entails (e.g., syntax validation, simulated result, or required permissions). The behavioral impact and return value are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence. However, it is too terse and omits critical details, reducing its effectiveness. While brevity is valued, it comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 params, no output schema, no annotations), the description is insufficient. It does not explain what 'preview' returns, how parameters relate, or how this tool fits among the many sibling preview tools. The description is far from complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no meaning to any of the 6 parameters (oid, name, sources, etc.). For example, 'sources' is not explained (URLs? file paths?). The description fails to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview creating or updating a YARA scanning rule' clearly states the tool's action: previewing a create or update operation on a YARA rule. It distinguishes from siblings like lc_preview_delete_yara_rule and lc_preview_set_yara_source by focusing on the rule itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives (e.g., lc_preview_set_yara_source, lc_preview_delete_yara_rule). There is no mention of prerequisites, when-not-to-use, or context that helps differentiate from the many sibling preview tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. 'Preview' implies a dry-run or simulation, but it does not state whether actual execution occurs, what the output represents, or if any side effects exist. The description lacks critical behavioral details for a mutation-like tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but vague. It misses opportunity to front-load key details like what 'preview' entails. A bit too short to be useful, but not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and 5 parameters with zero description coverage. The description fails to provide context about return values, prerequisites, or effects. Incomplete for a tool with this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter descriptions. The tool description does not describe any of the 5 parameters (oid, tag, task, selector, token_ttl_seconds). The agent must infer meaning solely from parameter names and types, which is insufficient for correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool previews running a fleet-wide spotcheck task, using a specific verb ('Preview running') and resource ('spotcheck task'). It distinguishes from sibling preview tools by specifying 'spotcheck', which is unique among the many lc_preview_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling preview tools (e.g., lc_preview_sensor_task, lc_preview_reliable_task), it does not explain the specific scenario for using spotcheck over other preview actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It does not explain the 'preview' behavior, such as whether it simulates the termination, requires confirmation, or has side effects. The agent is left to guess what the output or consequences are.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at five words, front-loading the purpose. However, it may be too terse, sacrificing necessary detail for brevity. It earns a high score for efficiency but loses a point for under-specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters, no output schema, and no annotations, the description is far from complete. It does not cover what the preview returns, how the parameters are used, or how this tool fits into the workflow (e.g., culminating in an actual termination via confirm_action).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description adds no information about parameters. The input schema has three parameters (oid, session_id, token_ttl_seconds) with no descriptions in either the schema or the tool description, leaving the agent with no guidance on their meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview terminating a running AI session' clearly states the action (preview terminating) and the resource (AI session). It is specific enough to distinguish from other tools, though it could be more precise about what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no prerequisites or conditions for use. The description solely states what it does without contextual advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description implies non-destructive behavior ('preview'), but it doesn't confirm side effects, permission requirements, or output characteristics. The behavioral impact is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
At four words, the description is concise but under-specifies. It front-loads the operation type, but omits critical details, making it insufficient for an agent to invoke correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters (one nested object) and no output schema, the description is severely incomplete. It doesn't explain the preview process, input requirements, or expected output, resulting in poor contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter meaning. extension_name, token_ttl_seconds, and extension_definition are undefined. The description fails to clarify their roles, leaving agents without guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it previews updating an extension definition. This distinguishes it from sibling preview tools like lc_preview_create_extension and lc_preview_delete_extension by specifying the operation type. However, it lacks detail on what 'preview' entails (e.g., validation, dry-run).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, the relationship to lc_get_extension, or whether direct update exists. The description provides no context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only states 'summarize', implying read-only, but does not mention side effects, permissions, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (two words in meaning), which is concise but sacrifices informativeness. It is not well-structured for understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and incomplete parameter descriptions, the tool description fails to provide a complete understanding of what the tool does or how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should explain parameters. Neither 'oid' nor 'limit' are described, leaving their meaning ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool summarizes case backlog and dashboard evidence, which distinguishes it from sibling review tools like lc_review_fleet_health. However, 'bounded' is vague and does not fully clarify the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavior. It states 'summarize' but does not disclose whether it is read-only, what side effects exist, required permissions, or the nature of the output. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that lists the domains, which is concise. However, it lacks structure to guide understanding, such as separating purpose from usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and two undocumented parameters, the description should provide more detail about the summary format and parameter roles. It is incomplete for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters (oid, limit). An agent cannot infer what oid represents or how limit affects results, making effective invocation nearly impossible.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'summarize' and specifies the resource as coverage evidence for D&R, FP, logging, integrity, YARA, and MITRE. It clearly indicates the tool's function but the term 'coverage evidence' is somewhat vague and doesn't fully distinguish it from other review tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any conditions or exclusions. The single sentence lacks any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It only states the action but not side effects, permissions, or whether it is read-only. For a summarization tool, it fails to clarify if it modifies state or just queries.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It is front-loaded but too short to cover necessary details, making it minimally acceptable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 4 parameters, the description should explain output format, pagination, or behavior. It only describes the high-level function, leaving the agent guessing about what the summary looks like or how limit affects results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters (oid, start, end, limit) with 0% schema description coverage. The description does not explain any parameter's meaning or format, so it adds no value over the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool summarizes bounded detection volume and concentration for a time window, using a specific verb and resource. It distinguishes from sibling review tools like lc_review_case_backlog by focusing on detection noise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks any context about prerequisites or scenarios, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It does not indicate whether the operation is read-only, what permissions are needed, or what the output looks like. The description is minimal and lacks transparency about side effects or dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence. While it avoids verbosity, it sacrifices needed detail. It is front-loaded with the action and resources, but additional context is missing. A 3 reflects that it is not wordy but is under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, the description is severely incomplete. It does not explain parameters, return values, or behavioral context. For a tool with two parameters and many siblings, more detail is essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has two parameters (oid, limit) with 0% description coverage. The description does not explain what 'oid' represents (likely an organization ID) or how 'limit' affects results. Without parameter documentation, an AI agent cannot determine how to properly invoke the tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('summarize') and the resources ('outputs, extension subscriptions, and feedback channel health'). It distinguishes from sibling listing tools like lc_list_outputs, lc_list_extension_subscriptions, and lc_list_feedback_channels by focusing on health summary rather than raw lists. However, the term 'summarize' is somewhat vague, and 'health' is not defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_list_outputs or other review tools). There is no mention of prerequisites, context for use, or when not to use this tool. The description offers no decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only hints at a read operation ('search') but does not disclose auth requirements, rate limits, or behavioral traits like case sensitivity or wildcard support, which are present in the schema but not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence, no wasted words. Efficient but could afford an extra sentence to clarify key parameters or expected use without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, no annotations, and no output schema, the description is critically insufficient. The agent lacks understanding of return values, parameter roles, and how 'prevalence or locations' manifests in results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description adds zero information about any of the 8 parameters (oid, obj_type, obj_name, info, limit, wildcards, per_object, case_sensitive). The agent cannot infer parameter meaning or usage from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'search' and the resource 'IOC/object', indicating it operates on a single IOC, differentiating from batch counterparts implicitly. However, the phrase 'Insight prevalence or locations' is somewhat vague, lacking concrete specificity about what exactly is returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_batch_search_iocs or lc_get_object_information. Missing prerequisites, use cases, or exclusions, leaving the agent to infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only says 'without saving it' but does not disclose side effects, permissions needed, return behavior on success/failure, or whether it modifies any state. With 12 parameters, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loading purpose. However, given the tool's complexity (12 parameters), it is too minimal and lacks structured detail. It is concise but under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is severely incomplete for the complexity: no explanation of validation process, return format, error handling, prerequisites, or relation to other Hive tools. Sibling tools exist but are not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, and the description adds no parameter meaning. Required fields like oid, hive_name, key, and data are unexplained. With 12 parameters, the lack of parameter info is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action 'validate' and the resource 'Hive record', and distinguishes it from siblings like lc_get_hive_record (retrieve) and lc_preview_set_hive_record (preview save). However, it does not clarify what 'validate' entails (e.g., schema check, business rules).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Among siblings, there are other validation tools (e.g., lc_validate_replay_rule) and preview tools that also don't save, but the description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a dry-run with minimal event (suggesting no side effects) but does not disclose permissions needed, error behavior, or whether the tool is read-only. The term 'Replay' is ambiguous without further explanation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 10 words, which is concise but too brief. It front-loads the purpose but omits critical details, making it minimally acceptable in terms of structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, a complex nested object (rule_content), no output schema, and no annotations, the description is severely incomplete. It does not cover return values, error handling, or parameter explanations, leaving the agent unable to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, with no parameter descriptions in the schema. The description fails to explain any parameter, including the required 'oid' and 'rule_content', or the optional 'trace', 'limit_evals', and 'limit_events'. This leaves the agent without guidance on how to populate the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates a D&R rule using Replay with a dry-run minimal event. It distinguishes from siblings like lc_replay_dry_run and lc_validate_search_query by specifying the validation context, but could be more explicit about what validation entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as lc_replay_dry_run. No prerequisites or context provided for the expected use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as idempotency, side effects, error behavior, or permission requirements. The term 'validate' implies a read-only check, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, which is efficient but lacks essential details. It could be expanded to include parameter context or usage hints without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and output schema, and the complexity of 8 parameters, the description is severely incomplete. It fails to explain what constitutes a valid mapping, what the output looks like, or how to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and no parameter details in the description, none of the 8 parameters (including required ones like oid and platform) are explained. The description adds no meaning beyond the schema field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (validate) and the resource (Universal Sensor Protocol mapping/input configuration). It is specific enough to differentiate from sibling validation tools like lc_validate_hive_record, lc_validate_replay_rule, and lc_validate_search_query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusion criteria, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that it starts a paginated search job, but does not mention whether it is read-only, the lifecycle of the job (e.g., need to poll), or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but omits critical details such as parameter meanings, return value, and usage context. It prioritizes brevity over completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with no descriptions, no output schema, and a complex operation (search job), the description is severely incomplete. It does not explain the job concept, how to poll results, or what inputs are valid.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the 5 parameters. Schema coverage is 0%, so the agent receives no guidance on what oid, name, start, end, or stream mean.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (load a saved query, start a paginated LCQL search job) and distinguishes from siblings like lc_execute_search_query (direct query execution) and lc_get_saved_query (retrieving definition).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies usage for executing a saved query, but does not mention when-not-to-use or point to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether the operation is read-only, requires specific permissions, has rate limits, or what format the export returns. The agent has no insight into side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no extraneous words. It efficiently conveys the core purpose, though additional structure (e.g., separating purpose from details) would improve readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too minimal. It does not explain what the sensor manifest contains, how the export is returned (e.g., file, data stream), or handle error cases. An agent would lack sufficient context to reliably use this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'oid' is not explained in the description. While the name suggests it is an org ID, the description does not confirm this or provide format details. With schema description coverage at 0%, the description fails to add meaning beyond the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Export) and the resource (full sensor manifest for an org). It distinguishes from sibling tools like lc_list_sensors by specifying 'manifest' rather than just listing. However, it could be more precise about what a 'sensor manifest' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_list_sensors or lc_find_sensors_by_hostname. The agent is left to infer the appropriate context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It only states the action without disclosing side effects, required permissions, rate limits, or return format. The read-only nature is implied but not explicit. Misses an opportunity to provide critical behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. However, it is overly minimal and could include more useful information without becoming verbose. Acceptable but not optimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and parameter descriptions, the description is severely incomplete. It fails to explain what a config value is, what the return looks like, or how it relates to other tools. An agent would struggle to use this tool correctly without external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description must add meaning to the parameters. However, it does not explain 'oid' (likely org ID) or 'config_name' (valid values or where to find them). The parameter names alone are insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get one organization config value' clearly states the verb and resource. It is specific and understandable, but does not differentiate from similar sibling tools like lc_fetch_config. The purpose is clear enough for an AI agent to understand the tool's basic function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or when to prefer it over other config-related tools like lc_fetch_config. The agent receives no help in tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose behavioral traits like read-only nature, permissions required, or return format. The minimal description does not compensate for lacking annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but under-specified. Lacks structure and additional context that could be added without bloat, such as parameter clarification or example usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and low schema coverage, the description is insufficient. It omits details about ordering, deduplication, pagination, or relationship to cases, making it hard for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 0% of parameter descriptions. The description only hints that 'for an org' relates to the 'oid' parameter but doesn't explicitly state that oid is the org ID or provide any additional constraints or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it lists unique case assignee emails for an org. Distinguishes from sibling list_case_* tools by focusing on assignee emails. However, it doesn't explicitly connect the 'oid' parameter to the org, which is implied.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives like lc_list_cases, lc_list_users, or other list tools. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits such as pagination, ordering, or the definition of 'entities'. The minimal description does not compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 6 words, but this brevity sacrifices necessary detail. It is front-loaded but insufficiently informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and parameter details, the description is grossly incomplete. The agent cannot determine the tool's full behavior or return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description adds no meaning to the required parameters 'oid' and 'case_number'. The agent must infer their roles from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (entities attached to a case), making the purpose understandable. However, it does not differentiate from the sibling tool lc_search_case_entities, which likely serves a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lc_search_case_entities. There is no mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden for behavioral disclosure. It fails to mention any side effects, authentication needs, error handling (e.g., if sensor not found), or read-only nature, providing no insight beyond the tool's purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. However, it is too minimal to be useful, scoring 3 as a middle ground between conciseness and under-specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and lack of output schema, the description should at least mention the parameters or provide context about return values. It does not, and with many sibling tools, more differentiation is needed to avoid confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but does not. The parameters oid and sensor_id are not explained, and the description adds no context about their format or role, leaving the agent entirely reliant on parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List tags applied to one sensor' clearly identifies the verb (list), resource (tags), and scope (one sensor), distinguishing it from sibling tools like lc_list_tags (which lists all tags globally) and lc_find_sensors_by_tag (which does the reverse).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use or when-not-to-use guidance is given. The description does not mention alternatives like lc_list_tags for global listing or lc_find_sensors_by_tag for searching sensors by tag, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only says 'preview' without explaining what that entails (e.g., non-destructive? what gets returned?). Minimal insight into side effects or operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but omits critical information. It is not just concise; it is underspecified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and a complex parameter set (nested object), the description is completely inadequate. It does not explain what the preview returns or how the tool fits into workflows.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 4 parameters including a nested object, the description adds no meaning beyond parameter names. No explanation of 'oid', 'detection', 'case_number', or 'token_ttl_seconds'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Preview) and the resource (linking a detection to a case). It is specific and distinguishes from sibling preview tools like lc_preview_add_case_artifact or lc_preview_add_case_entity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no information about when to use this tool versus alternatives, no exclusions, and no context on prerequisites or expected outcomes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description is the sole source of behavioral info. 'Preview deleting' implies a safe, non-destructive simulation, but there is no mention of what the preview returns, required permissions, or side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one phrase) but is under-specified. While front-loaded, it lacks essential detail, making it merely terse rather than effectively concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with no documentation, no output schema, and a bare-bones description, the tool definition is incomplete. An agent cannot effectively use this tool without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain any parameters (oid, name, token_ttl_seconds). The description adds no value to understanding parameter meaning or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Preview deleting' and the resource 'output integration', distinguishing it from other preview_delete_* tools. It is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_delete_output, lc_confirm_action, or other preview tools. The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should fully disclose behavior. It says 'Preview sending' which implies no actual send occurs, but it does not explicitly confirm that the operation is non-destructive, state side effects, or mention required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is too short to provide necessary context. While concise, it sacrifices clarity and completeness, leaving critical information missing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, no output schema, and zero annotations or parameter descriptions, the description is completely inadequate. It fails to provide enough information for correct tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description provides no explanation of any parameters. The agent is left to guess the meaning of fields like 'oid', 'channel', 'question', and 'feedback_destination'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Preview' and the resource 'external free-form question' via 'ext-feedback'. It differentiates from sibling tools like lc_preview_feedback_acknowledgement and lc_preview_feedback_simple_approval by specifying the type of feedback.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention the context for previewing or any prerequisites like needing a feedback channel setup.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It does not mention side effects, output format, authentication needs, or whether the operation is destructive. The term 'Export' implies a download but no details are given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no waste, but it lacks essential details. Its brevity sacrifices completeness for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and parameter descriptions, the description is insufficient. An AI agent needs to know what the export produces (e.g., file, URL) and whether it is synchronous or asynchronous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain the parameters 'oid' and 'case_number'. While it mentions the exported content, it fails to add meaning to the parameters beyond their names. With 0% schema description coverage, the description should have detailed parameter roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Export' and the resource 'a case' along with specific contents (detections, entities, telemetry, artifacts). It is more specific than a tautology, but it does not differentiate from sibling tools like lc_get_case or lc_list_case_*, as 'export' is not defined relative to them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_get_case or lc_list_case_*. There are no explicit when-to-use, when-not-to-use, or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It only states the action without disclosing behavioral traits such as read-only nature, auth requirements, or side effects. The agent cannot infer safety or expected behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
At only 5 words, the description is extremely concise but at the expense of necessary structure and information. It does not front-load key details or use formatting to aid comprehension. The brevity is harmful given the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of 2 required parameters with no descriptions, no output schema, no annotations, and no sibling differentiation, the description is incomplete. It fails to inform the agent about what the tool returns or how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema provides no descriptions for the two required parameters (oid, name). The tool description does not explain these parameters, leaving the agent without semantic understanding of what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one AI skill Hive record' clearly states the action (fetch) and resource (one AI skill Hive record). It is specific and distinguishes from sibling tools like 'lc_list_ai_skills' and 'lc_get_ai_agent'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives. It does not mention any prerequisites, context, or exclusions. Among many similar get tools, no differentiation is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or what happens for missing identities. The term 'bounded' is vague and not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence (9 words), which is concise but overly brief. It lacks structural elements like examples or clarifications. Every word earns its place, but important details are omitted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should be more thorough. It does not explain the return value, pagination via 'limit', or how to interpret 'bounded' usage. The tool is simple but the description leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no descriptions in the schema). The description only hints at the 'identity' parameter ('for one AI usage identity') but does not explain 'oid' or 'limit'. The agent lacks guidance on required formats or how parameters affect behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches token and cost usage for one AI usage identity. It distinguishes from sibling get tools (e.g., lc_get_ai_agent) by specifying 'usage' context. However, the term 'bounded' is ambiguous and could be clearer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like lc_list_ai_usage_identities. The description does not mention prerequisites, context, or exclusions, leaving the agent to infer applicability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only says 'fetch', implying a read operation but does not disclose any behavioral traits such as permissions required, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-informative. It earns its place but lacks necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (1 param, no output schema), the description should at least hint at the structure of the returned billing details. It only says 'detailed billing information', which is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'oid' has no description in the schema (0% coverage) and the tool description does not explain what 'oid' represents (presumably org ID). This leaves the parameter's meaning ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'detailed billing information for an org', which is distinct from siblings like lc_get_billing_status (status) and lc_get_billing_invoice_url (invoice URL). However, 'detailed' is vague and could be more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus related billing tools (e.g., lc_get_billing_status, lc_get_billing_invoice_url). No context or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description implies read-only but does not explicitly state it is safe or disclose side effects, permissions, or return format. For a tool with zero annotations, more transparency needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, efficient and front-loaded. However, it could include parameter explanations without being overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no output schema, and no annotations, the description is too sparse. It does not specify what statistics are returned, the type of count, or behavior of is_detailed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 5 parameters with 0% description coverage. The description does not explain any parameter, such as the meaning of is_detailed or the format of start/end timestamps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches retained event count/statistics for one sensor and a time window. It uses specific verbs and resources distinguishing it from general event listing tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_get_sensor_event_overview or lc_list_sensor_events. No when-not or prerequisite information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden for behavioral disclosure. 'Fetch' implies a non-destructive read operation, but no details are given about idempotency, error states, or authorization requirements. The description is too terse to compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. While concise, the brevity results in omitted critical information. It earns a 4 for structure but is undermined by lack of content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 required params, no output schema), but the description fails to provide essential context about parameter usage and return expectations. An agent cannot reliably use this tool without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two required parameters (oid, name) with 0% description coverage in the schema. The description does not explain what these parameters represent or how to use them, leaving the agent with only parameter names to infer meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one lookup Hive record' clearly states the action (fetch) and the resource (lookup Hive record). It distinguishes from siblings like lc_list_lookups (lists lookups) and lc_get_hive_record (general Hive record fetch). However, it could be more explicit about what makes 'lookup' records distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_list_lookups or lc_get_hive_record. The description does not mention prerequisites or context for using 'lookup' specifically.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full behavioral disclosure burden. It only states 'Fetch' (a read operation) but omits any behavioral traits such as authorization needs, error behavior, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence that front-loads the purpose. However, it is so brief that it omits important details, trading conciseness for completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, zero parameter descriptions, and no annotations, the description is highly incomplete. A simple fetch tool may afford brevity, but the generic parameter names 'oid' and 'name' require clarification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%; the description adds no meaning to the parameters 'oid' and 'name'. It does not explain what these identifiers represent or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetch') and resource ('playbook Hive record'), clearly indicating retrieval of a single playbook record. It indirectly distinguishes from sibling list tools like lc_list_playbooks, but does not explicitly differentiate from other get tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Among many sibling 'get' tools, the description does not specify selection criteria or contrast with tools like lc_get_hive_record.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states the action without indicating side effects, error handling, permissions required, or whether the operation is read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief at one sentence, but it sacrifices necessary detail for brevity. It front-loads the action but fails to provide any structural separation or additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two required parameters, no output schema, and no annotations, the description is inadequate. It does not explain the return value, the significance of both parameters, or the expected behavior in edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions only the 'name' parameter as a retrieval key but does not explain the 'oid' parameter, which is also required. This leaves the agent unclear about the role of 'oid'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and resource 'one saved LCQL query', but it only mentions retrieval 'by name' while the schema requires both 'oid' and 'name' parameters, slightly omitting the necessary context of organizational scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings, such as `lc_list_saved_queries` or `lc_execute_saved_query`. There is no mention of prerequisites or alternative contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are present, the description must fully disclose behavioral traits. It implies a read-only check but does not explicitly state that it does not modify sensor state, nor does it explain what 'sealed' means or what the response format is. More context is needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is overly minimal to the point of being insufficient. While it avoids verbosity, it sacrifices essential details, so it earns a middle score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has two required parameters and no output schema, the description provides almost no help. It does not explain the parameters, the return value, or any side effects. An agent would be left guessing how to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about the required parameters 'oid' and 'sensor_id'. Without any semantic explanation, the agent cannot determine how to fill these fields correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check whether one sensor is currently sealed' uses a specific verb ('check') and clearly identifies the resource ('sensor seal status'). It distinguishes itself from sibling tools like lc_get_sensor (general info) and lc_get_sensor_isolation_status (isolation status), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, or any prerequisites. For a simple read operation, one might expect at least a note that it is non-destructive, but nothing is stated. This leaves the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'Fetch', implying read-only, but does not explicitly state idempotency, permissions, or side effects. Insufficient for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, but at the cost of missing crucial information. Could add parameter context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and a very brief description. The agent lacks information about return values, error conditions, or any operational constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain what parameters 'oid' and 'name' represent. The agent has no information to correctly populate these required fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Fetch' and resource 'one SOP Hive record', distinguishing it from siblings like lc_get_hive_record and lc_list_sops.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as lc_get_hive_record or lc_list_sops. The description is purely functional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral traits beyond the trivial implication of listing. With no annotations, the description carries full burden but fails to mention side effects, authentication needs, or return nature. It is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, very concise, and front-loaded with the action. It wastes no words, though it might be overly brief for a tool with a parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity (one optional param, no output schema), the description lacks completeness. It does not hint at return values or what 'available billing plans' entails, leaving ambiguity about the output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (no parameter descriptions). The description does not explain the 'limit' parameter, nor does it add any meaning beyond the schema. It fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List available billing plans.' It uses a specific verb ('List') and resource ('billing plans'), distinguishing it from sibling billing tools like lc_get_billing_details and lc_get_billing_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Sibling tools like lc_get_billing_details might be more appropriate for detailed plan info, but the description provides no such context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose any behavioral traits beyond listing, such as side effects, rate limits, or idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but minimal. Could include more detail without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No annotations or output schema; description lacks details like return format, pagination, or maximum limit. Incomplete for a list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning for OID (org-key JWT scope) but ignores the limit parameter. With 0% schema coverage, more parameter context is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists LimaCharlie event types, with an optional OID parameter. The name is explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives, nor when not to use it. Only mentions optional OID usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the basic function and does not mention whether the operation is read-only, requires specific permissions, pagination behavior, or response format. This leaves critical gaps for safe and correct usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise without fluff. However, it is too brief to provide necessary details, sacrificing completeness for brevity. It earns a middle score because while efficient, it is under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and incomplete parameter descriptions, the description should cover return values and behavior. It fails to explain what the list returns, pagination, or error scenarios, making it insufficient for an agent to use confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning no parameter descriptions are provided in the schema. The description only adds the context of 'for an org' (implying oid is the org ID) but does not explain the oid parameter's format or the limit parameter's effect. Little value is added beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (integrity monitoring rules) with scope (for an org). However, it does not explicitly distinguish from sibling tools like lc_get_integrity_rule (which retrieves a single rule) or other list tools, though the naming convention implies the difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor are there any prerequisites or context about the org parameter. The description lacks any usage recommendations or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the basic purpose without disclosing behavioral traits such as required permissions, whether errors are live or historical, ordering, or whether resolved errors are included. This is insufficient for a list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but overly minimal. While it has no extra words, it lacks important context. Conciseness is achieved at the expense of completeness, which is not ideal for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one required parameter, no output schema, and no annotations, the description is grossly incomplete. It does not explain the oid parameter, does not describe the output format, and provides no context about error types or prerequisites. This is inadequate for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the single parameter 'oid'. The parameter name suggests organization ID, but no clarification is given. The description adds no value beyond the schema, failing to compensate for low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists current organization component errors, using the specific verb 'List' and resource 'organization component errors'. The word 'current' adds temporal context, distinguishing it from other list tools like lc_list_org_notes which list different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There are many sibling list tools (e.g., lc_list_orgs, lc_list_org_notes) but the description does not differentiate when to choose this one over them. No usage context or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as pagination, ordering, or whether it is read-only. The lack of transparency forces the agent to assume basic list behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it lacks necessary detail to be fully informative. It is concise but at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and only two parameters, the description fails to cover what the tool returns or how to interpret results. With sibling tools like lc_preview_create_output and lc_review_output_health, the agent needs more context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain the meaning or role of the 'oid' and 'limit' parameters. 'oid' likely refers to org ID but is not clarified, and 'limit' though self-evident could benefit from scope specification.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and the resource (output integration configuration) and scopes it to an org. However, it does not differentiate from other list tools among siblings, and the term 'output integration configuration' may be ambiguous without context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_list_cases or lc_review_output_health. No context about prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavioral traits. It only states that CVEs are listed from sensors, without mentioning pagination, required parameters (oid), or any other behavioral details. The description is insufficient for understanding tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) with no waste, but it lacks structure and is too brief to be helpful. It could be considered minimal, earning an average score for conciseness but poor for informativeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 10 parameters (1 required), no output schema, and many sibling tools, the description is severely incomplete. It does not cover pagination, filtering, sorting, or any usage context. The agent would lack critical information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameter descriptions are empty. The tool description does not add any meaning to the parameters (e.g., oid, limit, cursor, search, filters, etc.). The agent receives no help in understanding what each parameter does.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'CVEs', and specifies they are 'observed across the org's sensors through ext-vulnerability-reporting.' This distinguishes it from sibling tools like lc_list_vulnerability_cve_hosts, which list hosts rather than CVEs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing CVEs but provides no explicit guidance on when to use this tool versus alternatives (e.g., other vulnerability list tools) or when not to use it. No exclusions or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It only says 'preview', hinting at non-destructive behavior, but does not explain side effects, authentication needs, rate limits, or what the preview entails. Insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, making it concise. However, it lacks structure and is too brief for a tool with many parameters; it does not earn its place by providing essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, 4 required, no output schema) and the presence of many siblings, the description is incomplete. It does not explain what the preview returns, how to interpret results, or any further context needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about the 8 parameters beyond their names in the schema. No explanation of oid, case_number, path, source, or optional fields like note, verdict, artifact_type, token_ttl_seconds.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview adding), resource (forensic artifact reference), and target (case). It distinguishes from other preview tools by specifying 'forensic artifact reference', but does not explicitly differentiate from similar siblings like lc_preview_add_case_detection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention that this is a dry-run or provide context on prerequisites, conditions, or exclusions. Given many preview siblings, explicit usage guidelines are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states 'Preview adding' implying no actual modification, but does not explicitly confirm it is read-only or safe. Important behavioral details like whether the tool requires permissions, returns a list of tags, or locks the case are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but too brief given the lack of other documentation. It could be improved by adding a second sentence to clarify behavior or parameters without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no explanation of what a 'preview' returns, the description is incomplete. It does not mention the relationship to confirmation tools or what the agent should expect as a response. The tool's role in the broader context of tag management is unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning to parameters. It only mentions tags and case in general, leaving 'oid' and 'token_ttl_seconds' unexplained. The phrase 'the exact merged tag list' refers to the result, not the parameter. Without descriptions, the agent cannot interpret parameter roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'preview adding' and identifies the resource 'tags to a case'. It distinguishes from siblings like 'lc_preview_set_case_tags' and 'lc_preview_remove_case_tags' by the action type. However, 'replacing the exact merged tag list' is ambiguous as it could mean showing the merged result or actually replacing in the preview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings or how it fits into a workflow (e.g., before confirming with another tool). No context about expected usage or alternatives is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It implies a dry-run operation but does not explicitly state that no group is created, what permissions are checked, or what the response contains. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single concise sentence, no fluff. But could benefit from slightly more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, description lacks essential completeness. Agent needs to know this is a non-mutating preview, expected return format, and parameter details. All are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and description adds no meaning to parameters. 'name' and 'token_ttl_seconds' are not explained; agent must guess their roles. For a preview tool, token_ttl_seconds is particularly unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Preview creating' and resource 'organization group', distinguishing it from sibling tools like lc_preview_delete_group. However, 'preview' is somewhat vague and could be more precise about what previewing entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Sibling list includes many preview tools, but description provides no context on when previewing group creation is appropriate or what steps precede it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior fully. It implies a non-destructive preview but fails to state whether the action modifies state, requires permissions, or has side effects. The preview's output and behavior are not described, leaving the agent uncertain about safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence. However, it is too brief for a tool with three parameters and no annotations, omitting important details that would justify its length. It achieves conciseness but at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and low schema coverage, the description is inadequate. It does not explain the return value, the meaning of 'preview,' or parameter usage, leaving significant gaps for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not add any meaning to the parameters (oid, name, token_ttl_seconds). The schema provides only titles, which are insufficient for an agent to understand parameter usage, such as what 'oid' refers to or how 'token_ttl_seconds' affects the operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the verb 'Preview deleting' and the resource 'external adapter Hive record,' which distinguishes it from other preview_delete_* siblings. However, it does not explain what 'preview' means in this context, leaving ambiguity about whether it simulates deletion or shows consequences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as a direct delete tool or other preview_delete_* tools. There is no mention of prerequisites, conditions, or when-not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states 'Preview deleting', which implies a non-destructive read-like operation, but it does not explicitly confirm idempotency, side effects, or what happens if the query does not exist. The meaning of 'preview' (e.g., returns a confirmation token or simply a dry-run result) is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that concisely conveys the core action. It is appropriately sized for a simple tool, though adding a bit more detail would improve it without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters and no output schema, the description is incomplete. It does not explain what the preview returns, how to interpret the result, or how the parameters identify the query. Users are left guessing about the tool's behavior and output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should clarify parameters. It lists `oid` and `name` as required but does not explain their roles or why both are needed. The optional `token_ttl_seconds` is not mentioned. The description adds no value to parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool does a 'preview deleting' of one saved LCQL query, which is a specific verb-resource combination. It distinguishes from sibling tools like `lc_delete_saved_query` (actual deletion) and `lc_list_saved_queries` by its preview nature, though it does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives such as `lc_execute_saved_query` or `lc_get_saved_query`. There is no mention of prerequisites, when to preview versus actually delete, or what context the preview is useful for.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose whether the preview is safe, what side effects occur (e.g., token creation), or the destructive potential. The name suggests deletion, but the preview nature is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but omits important details. It could be expanded without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a preview workflow typical in this system, the description lacks critical context such as what the output is, how to use the token, or the relationship to confirm/cancel actions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage). The description does not explain any parameter beyond their names. Parameter names are self-evident but no additional semantic value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting one sensor record' clearly states the action (preview delete) and the resource (sensor record). It distinguishes from sibling preview_delete tools by specifying the entity type in both name and description. However, it does not clarify what 'preview' means operationally.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_confirm_action or lc_cancel_action. There is no mention of prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It only says 'preview deleting' but does not explain what that entails (e.g., simulation, confirmation, no side effects). This is insufficient for an agent to understand the tool's action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is short, it is under-specified. Every sentence should add value, but this single sentence omits critical details, so it is not appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low schema coverage, no output schema, and many sibling tools, the description is incomplete. It fails to explain the preview behavior, return value, or prerequisites, making it inadequate for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it does not mention any parameters. The agent gets no information about what oid, name, or token_ttl_seconds mean, leaving them ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's purpose: previewing deletion of an SOP Hive record. The verb 'preview deleting' and resource 'SOP Hive record' are specific and distinguish it from sibling preview delete tools for other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this preview tool versus actual deletion or other sibling tools. No prerequisites or alternatives are mentioned, leaving the agent without context for appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It does not disclose that 'preview' is non-destructive, nor explain token_ttl_seconds or any side effects. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and front-loaded. However, it is too brief for the complexity; additional sentences would be justified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and minimal description. For a preview tool, agent lacks knowledge of returned data, required permissions, and parameter semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet description adds no meaning beyond parameter titles. 'oid', 'case_number', 'detection_id', and 'token_ttl_seconds' remain unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description 'Preview removing a detection link from a case.' clearly states the verb and resource, distinguishing it from add/confirm siblings. However, it could be more explicit about what 'preview' entails (e.g., returns potential changes without applying them).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this preview vs. alternative actions (e.g., confirming the removal). No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'preview,' suggesting a read-only operation, but does not explain return format, permissions, or safety implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but overly terse. It front-loads the purpose but provides no additional structure or detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, and no annotations, the description lacks completeness. It does not explain the preview concept, output, prerequisites, or behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides no insight into parameters like oid, new_name, or token_ttl_seconds, failing to add meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview renaming an org.' clearly states the verb (preview) and resource (org), distinguishing it from siblings like lc_check_org_name and lc_preview_create_org.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It implies a preview before rename but lacks context about prerequisites or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The term 'Preview' is ambiguous—it could imply a dry-run or an actual toggle. The description does not clarify side effects, whether the action is reversible, or if authentication is needed. With no annotations, the transparency is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, effectively concise. However, it sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters and no output schema, but the description omits return behavior, confirmation of success, or relationship to the broader AI skill lifecycle. Incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no explanation for parameters (oid, name, enabled, token_ttl_seconds). The agent receives no guidance on what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview toggling) and the resource (AI skill Hive record's enabled metadata), distinguishing it from broader tools like lc_preview_set_ai_skill.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_preview_set_ai_skill or other preview_set_X_enabled tools. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation via 'Preview', but it does not explicitly state that no changes are made. With no annotations, the agent gets insufficient disclosure about behavior, such as side effects or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundancy, but it is too brief to convey necessary information. It sacrifices clarity for brevity, making it minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, no annotations), the description is incomplete. It fails to explain the 'preview' concept, parameter semantics, or how it compares to many similar sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'enabled metadata' but does not explain the roles of 'oid', 'name', or 'token_ttl_seconds', leaving the agent to infer from parameter names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Preview') and resource ('lookup Hive record's enabled metadata'), making the core action clear. However, it does not differentiate from sibling tools like lc_preview_set_hive_record_enabled or lc_preview_set_lookup, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose that this is a preview (dry-run) operation or any behavioral aspects like auth requirements or side effects. The word 'preview' implies non-destructiveness but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. However, it is too brief to cover essential information, but from a conciseness perspective, it scores well.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and minimal description, the tool lacks necessary context about what the preview returns or what conditions are required. Incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain any parameters (oid, name, enabled, token_ttl_seconds), leaving their meaning entirely up to the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it previews toggling the enabled metadata of an organization-note Hive record, distinguishing it from setting the entire org note. However, 'preview toggling' could be more explicit about the action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs siblings like lc_preview_set_hive_record_enabled or lc_preview_set_org_note. No preconditions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. 'Preview' implies a trial run, but it does not clarify if this is an idempotent read-only check, what the preview yields, or whether it mutates state. Missing details like authorization requirements or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) and front-loaded with the key action. However, it sacrifices necessary detail for brevity, resulting in under-specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal parameter descriptions, the description is incomplete. It lacks details on what the preview outputs, how to interpret the result, prerequisites, and any side effects or confirmations needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameter meanings. It only mentions 'sensor quota for an org' without defining 'oid', 'quota' units/format, or the optional 'token_ttl_seconds'. This leaves the agent unable to correctly populate parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview setting) and the resource (sensor quota for an org). It is specific and distinguishes itself from many other lc_preview_set_* sibling tools by naming the exact resource and context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. There are many sibling preview_set tools, but no differentiation or usage context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only says 'preview' but does not explain behavioral traits like whether it performs validation, simulates changes, checks permissions, or has side effects. No disclosure of auth needs or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise, but it lacks key information and does not front-load the most critical details. It is underspecified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters with no schema descriptions, no output schema, and no annotations, the description is highly incomplete. It does not cover what the tool returns, how to interpret results, or how it fits with sibling tools like lc_set_secret_enabled.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain the meaning of any parameters (oid, name, tags, comment, secret_value, token_ttl_seconds) beyond their names. Agents are left to infer from parameter names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action (preview) and resource (secret Hive record). It distinguishes from siblings like lc_get_secret and lc_preview_delete_secret through the verb and resource, but does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when to use actual creation/update instead, or what 'preview' entails.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates it is a preview (non-destructive), but lacks details on behavior: what the preview shows, permissions needed, or side effects. With no annotations, the description should provide more context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise, but it is too brief to be informative. It sacrifices clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and 0% parameter coverage, the description is woefully incomplete. It does not explain what the preview returns, how to interpret results, or parameter relationships.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not explain any of the five parameters (oid, version, is_sleep, is_fallback, token_ttl_seconds). The description adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Preview changing the org sensor version policy.' It specifies the verb 'preview' and the resource 'org sensor version policy', distinguishing it from other preview tools among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_preview_set_playbook or other preview tools. No when-not-to-use scenarios or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states 'summarize', implying a read operation, but does not confirm read-only nature, required permissions, or any side effects. This is insufficient for safe agent use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. However, it is too brief, missing necessary detail. It earns its place but could be expanded without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no parameter explanations, the description fails to provide a complete picture. The term 'bounded sensor' is unexplained, and the tool's output format is unclear. For a review tool among many siblings, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning fields have no descriptions in the schema. The description does not explain what 'oid' or 'limit' represent, requiring the agent to infer from names. This is a significant gap for correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Summarize' and identifies the resource as 'bounded sensor and online-sensor evidence' for fleet health review. It distinguishes from sibling tools that list or get items, but the term 'bounded sensor' is unclear and could be more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There are no prerequisites, conditions, or exclusions mentioned, leaving the agent without context for appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that secrets are not exposed, which is a safety guarantee. However, with no annotations, it does not mention any other behavioral traits like read-only nature, rate limits, or whether it triggers any cached state changes. The safety note adds value but is not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) with no wasted words. It front-loads the key action ('Show') followed by what is shown. While efficient, it could benefit from a bit more structure, but it is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal parameter documentation, the description is incomplete. It does not explain the output format, the meaning of the credential mode and JWT status, or how the oid parameter affects results. An agent would need to infer or guess.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter (oid) has a schema coverage of 0% and the description does not explain its purpose, format, or effect. The agent has no way to know whether oid is needed or what it does, making this parameter effectively undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool shows 'credential mode and cached JWT status' and explicitly notes it does not expose secrets, which is a distinct purpose. However, it does not differentiate from sibling tools like lc_auth_refresh or lc_auth_whoami, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description implies it is for checking auth status without side effects, but there is no explicit 'when to use' or 'when not to use' advice, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only states the basic cancellation action. It does not disclose effects on query results, reversibility, or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence, 7 words) but communicates core purpose. It could be more structured but is acceptable for a simple cancellation operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and 0% param coverage, the description is incomplete. It fails to explain what the parameters are or the outcome of cancellation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters 'oid' and 'query_id'. The agent has no guidance on what these values represent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Cancel') and the resource ('a running LCQL search job'), distinguishing it from siblings like lc_execute_search_query and lc_poll_search_query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_cancel_action, nor does it specify prerequisites or context like when a query can be cancelled.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It fails to explain what happens if both 'oid' and 'name' are provided (required), or any side effects, permissions, or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one sentence that front-loads the verb. However, it is too brief and sacrifices necessary detail for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of a 'get' tool, the description is minimally adequate. However, with no annotations or output schema, it should provide more context about the record structure or behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description adds no meaning to the parameters 'oid' and 'name'. It does not clarify their roles or how they are used to identify the AI agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'one AI agent Hive record', making the tool's purpose evident. However, it does not distinguish itself from the sibling tool 'lc_get_hive_record', which also fetches a Hive record but is generic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'lc_get_hive_record' or other AI agent tools. The description lacks any context about prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully disclose behavioral traits. It only states 'fetch' but lacks details on side effects, auth needed, rate limits, or whether it modifies state. It does not add beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with 9 words is concise and front-loads purpose, but is too brief to convey necessary details. It is under-specified rather than efficiently complete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters, no output schema, and no annotations, the description does not explain what a 'full ai_memory record' contains, how parameters relate, or what the return value looks like. Incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 0% and description adds no meaning beyond schema. Parameters 'oid', 'agent', 'partition_key' are unexplained. The description fails to clarify their roles or expected formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'Fetch' and resource 'full ai_memory record for an agent', clearly distinguishing from listing or partial retrieval tools like lc_list_ai_memory_records or lc_get_ai_memory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no prerequisites, no exclusions. The description does not help an agent decide between this and sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'check,' implying read-only, but does not confirm safety, permissions, or side effects. Provides minimal transparency beyond the implied read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Perfectly concise: one sentence front-loads the tool's purpose with no fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and only one parameter, the description is too brief. It fails to specify the return type or additional context needed for an agent to correctly interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'oid' parameter. The parameter name alone is insufficient; the description should clarify that 'oid' is the org ID or similar.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it checks whether Insight retention appears enabled for an org, providing a specific verb (check) and resource (Insight retention status). However, it does not explain what 'Insight retention' is, which may require context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, conditions, or scenarios where this tool is preferable over other insights-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. However, it only states 'Fetch one service job' without indicating whether it is read-only, what happens if the job does not exist, or any permission requirements. This leaves critical behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it is too terse to be informative; it sacrifices clarity for brevity. A minimal viable description should at least hint at the required parameters or the context of 'service job'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (fetching a single resource) and the lack of output schema, the description should explain what a 'service job' is and clarify the parameters. It fails to do so, leaving the agent with insufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two required parameters (oid, job_id) with 0% schema description coverage. The description adds no information about these parameters, such as their purpose or expected format. The agent has no guidance on what values to provide for oid or job_id.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one service job' uses a specific verb ('Fetch') and clearly identifies the resource ('one service job'). It distinguishes itself from sibling tools like 'lc_list_jobs' (lists all jobs) and 'lc_wait_job' (waits for a job), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention siblings like 'lc_list_jobs' for retrieving multiple jobs or 'lc_wait_job' for monitoring job progress. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavior such as read-only nature, authentication requirements, or return format. The agent has no insight into side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure and additional context. It is not well-organized beyond being brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple tool with no output schema and no annotations, the description fails to provide sufficient context about the report's content or how to interpret the results. It is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter oid has no description in schema (0% coverage) and the description does not explain its meaning or format. The agent is left to guess what oid refers to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (Fetch), the data type (MITRE ATT&CK coverage data), and scope (for an org). It is distinct from sibling tools like lc_get_org_info or lc_get_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No information on when to use this tool versus alternatives, no prerequisites or context for usage provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only indicates a read operation ('Fetch'), but with no annotations provided, it should disclose more behavioral traits such as whether it returns large datasets, rate limits, or requires specific permissions. It lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. However, it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description is too brief to fully inform an agent. It does not explain what runtime metadata is, what the output contains, or how the parameters interact.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only vaguely references 'explicit org' and 'optionally filtered by entity', leaving out the 'limit' parameter and the distinction between entity_name and entity_type. It does not add significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch runtime metadata for an explicit org', which is a specific verb+resource combination. It distinguishes itself from sibling 'lc_get_*' tools by specifying runtime metadata, but does not elaborate on what constitutes runtime metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_org_info or lc_get_org_config_value. There is no mention of when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must disclose behavior. It states 'Fetch' (implies read-only), but fails to describe the response format (e.g., aggregated counts vs. raw events), pagination, or ordering. The term 'overview' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence without fluff, but could benefit from structuring with bullets or additional context while remaining concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool requires 4 parameters, no output schema, no annotations. Description is too minimal for an agent to confidently invoke. Missing details on return type, error cases, and parameter constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description carries full burden. It maps 'one sensor' to sensor_id and 'time window' to start/end, but does not explain oid (organization ID), or the format of start/end (e.g., epoch seconds). Insufficient to compensate for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action (Fetch), resource (event timeline overview), and constraints (one sensor, time window). However, it does not differentiate from siblings like lc_get_event (single event) or lc_list_sensor_events (list events).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. No preconditions, exclusions, or example use cases provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the purpose but does not mention pagination, result structure, authentication requirements, rate limits, or that this is a read-only operation. The schema implies pagination via limit and cursor, but the description omits this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the purpose with no extraneous words. However, it sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to mention pagination, filtering, required fields, or return structure, making it difficult for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of any parameters. It does not mention that 'oid' is required, nor does it clarify the roles of 'limit', 'cursor', or 'status'. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'AI sessions', the scope 'org-scoped', and the purpose 'governance and cost visibility'. This distinguishes it from sibling list tools like lc_list_ai_agents or lc_list_ai_memories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It does not state when not to use it or mention any prerequisites or context for governance and cost visibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full responsibility for behavioral disclosure. It only states it lists rules, but fails to mention that it is read-only, whether pagination applies, or what the response format is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, but it may be too brief given the lack of parameter descriptions and behavioral context. Every word earns its place, but additional sentences would improve completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotations, and minimal parameter info, the description is incomplete. It does not clarify what a successful response contains or how to handle pagination, making it insufficient for complex use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, leaving both parameters (oid and limit) unexplained. The description adds no parameter details beyond implying oid identifies the org.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List) and resource (artifact collection rules) and specifies the scope (for an org). It distinguishes from siblings like lc_list_artifacts and lc_get_arl, though the term 'artifact collection rules' could be more defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not specify when to use this tool over alternatives like lc_get_arl or lc_preview_set_artifact_rule, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'one bounded page' but does not explain pagination mechanics (e.g., cursor vs offset). It implies read-only behavior but does not explicitly state safety, side effects, or required permissions. The term 'bounded page' is ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundancy. It effectively uses front-loading by stating the action first. While brief, it could be expanded without becoming verbose, but it is efficient for a simple listing tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and low schema coverage, the description is insufficient. It does not explain return structure, artifact types, or pagination details. The tool has many siblings and moderate complexity, requiring more contextual information for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It maps 'org' to oid, 'sensor' to sensor_id, 'time window' to start/end, and 'cursor' to cursor, which adds value. However, it omits the 'limit' parameter and does not clarify if filters are combined or exclusive. The description only partially addresses the 6 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'List' and resource 'artifacts', and mentions 'one bounded page' indicating pagination. It lists possible filters (org, sensor, time window, or cursor), which helps clarify scope. However, it does not distinguish from the many sibling list tools or clarify what artifacts are exactly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_list_case_artifacts, lc_list_detections). There are no prerequisites, exclusions, or contextual hints. The description is generic and does not help an agent decide between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only states the basic function. It does not mention permissions, read-only nature, pagination, or any constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence, but it lacks necessary detail and structure. It is functional but minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with two required parameters and no output schema, the description fails to provide critical context about parameter semantics, output format, or any filtering behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds no information about the parameters 'oid' and 'case_number', leaving their meaning and usage entirely unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List detections linked to a case' clearly states the verb (list), resource (detections), and context (linked to a case), distinguishing it from the sibling tool 'lc_list_detections' which likely lists all detections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'lc_list_detections' or 'lc_get_detection', nor does it mention prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states the action without disclosing behavioral traits like permissions, safety (read-only), or what happens with missing parameters. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, no fluff, but it sacrifices informativeness for brevity. It could include more context without being overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no parameter descriptions, the description is incomplete. It fails to clarify what 'metadata' includes, the return format, or behavior for edge cases. A list tool typically needs more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain parameters. 'oid' and 'limit' are not described. The description adds no meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'installation key metadata', and the scope 'for an org'. It distinguishes from sibling tools like 'lc_get_installation_key' (which retrieves a single key) and other 'list_*' tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lc_get_installation_key for a specific key, or other list tools). No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It implies a read-only operation but does not explicitly state safety, pagination behavior, or what happens if no rules exist. The description lacks transparency about the tool's behavior beyond listing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. It contains no unnecessary words. However, it could expand slightly to cover basic parameter hints without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with two parameters and no output schema, the description is minimally adequate. It covers the core action but lacks context on output format, constraints, or error conditions. Not severely incomplete, but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds no meaning to parameters. It mentions 'for an org' but does not explain 'oid' (required) or 'limit' (optional with default). The agent cannot infer their meanings from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'logging collection rules' for an org. It is not a tautology and distinguishes from other list tools by specifying the resource, but it lacks explicit differentiation from sibling tools like lc_list_dr_rules or lc_list_fp_rules.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, use cases, or when not to use it. Given the large number of sibling list tools, this omission is significant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It does not mention whether the operation is read-only, has pagination, or requires specific permissions. The meaning of 'pending' is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence but lacks structure and additional context. It is under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal parameter info, the description fails to provide sufficient context for an agent to understand the tool's behavior, return type, or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not describe the 'oid' or 'limit' parameters. 'oid' is implied as the org identifier but not explicitly stated. 'limit' is not mentioned at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List'), the resource type ('pending reliable-tasking extension tasks'), and the scope ('for an org'). This distinguishes it from other list tools like lc_list_extension_subscriptions or lc_list_pending_actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lc_preview_reliable_task or other list tools. The description does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the basic function without disclosing behavioral traits like authentication needs, rate limits, pagination, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded, but lacks structure and essential details, making it borderline too brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and the description omits return format, pagination, and constraints. While a simple list tool, it needs more context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters (oid and limit) or their semantics. The agent must rely solely on the schema, which lacks descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List users with access to an org.' with a specific verb and resource, and it implicitly distinguishes from siblings like lc_list_user_permissions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no exclusions, and no context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only says 'list', implying read-only, but does not mention permissions, pagination behavior, or that it requires a valid oid and cve. No side effects are stated, but the lack of detail is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 8 words, very concise. It front-loads the key action and object. However, it sacrifices necessary detail for brevity, so it is not ideal. Still, for conciseness alone, it scores high.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, 2 required, no output schema, and no annotations, the description is severely incomplete. It does not explain the role of oid, the pagination mechanism, or the return format. A minimal description should at least mention that oid is an organization identifier and that results can be paginated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no parameter descriptions), and the description does not compensate. It does not explain the required parameters oid and cve, nor optional parameters like limit, cursor, sort_by, sort_asc, or include_enrichment. The only hint is that cve is a CVE identifier, but oid is entirely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists package/version pairs affected by one CVE. It specifies the resource and the filter, distinguishing it from sibling tools like lc_list_vulnerability_cve_hosts (which lists hosts) and lc_list_vulnerability_cves (which lists CVEs).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives. For example, it does not explain that this tool is for listing packages for a specific CVE, while lc_list_vulnerability_cve_hosts lists hosts for a CVE. The description is silent on prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The word 'preview' hints at a dry-run behavior, but the description does not confirm that no actual changes are made, what the output looks like, or any side effects. With no annotations to fill the gap, the agent lacks behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but not well-structured. It conveys the purpose but omits necessary details, making it barely adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description should explain what a preview operation entails (e.g., no actual changes, returns predicted outcome). It fails to provide this context, leaving the tool's behavior ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage for parameters. The description does not explain the meaning of 'email', 'group_id', or 'token_ttl_seconds'. An agent cannot infer correct usage from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview adding') and the resource ('a user as a group owner'). It is specific enough to distinguish from sibling tools like lc_preview_add_group_member or lc_preview_remove_group_owner.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not explain when to choose preview_add_group_owner over preview_add_group_member, nor does it mention any prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden of behavioral disclosure. It states 'preview deleting' implying no permanent change, but it does not confirm read-only nature, auth needs, or side effects. The parameter `token_ttl_seconds` is not explained, leaving ambiguity about its role in the preview operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise and front-loaded. However, it lacks necessary detail (e.g., what a preview entails, parameters role). It is not overly verbose, but could incorporate more information without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, preview operation, no output schema), the description is insufficient. It fails to clarify the return value (likely a confirmation or simulation result), the meaning of token_ttl_seconds, and how this preview differs from actual deletion. Important context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description adds no explanation for the three parameters (oid, name, token_ttl_seconds). While oid and name are intuitively identifiers, token_ttl_seconds (default 300) is entirely unexplained, forcing the agent to guess its meaning (likely TTL for a token used in the operation).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting an AI agent Hive record' clearly states the specific action (preview delete) and the resource (AI agent Hive record). It distinguishes from sibling tools like lc_preview_delete_hive_record (generic hive record) and lc_get_ai_agent (get, not preview delete). The verb 'preview deleting' accurately conveys a dry-run operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., existence of the agent), when not to use it, or that it should be followed by an actual delete tool like lc_confirm_action or lc_delete_ai_agent. Sibling tools for previewing other deletions exist, but no differentiation is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description signals that this is a preview (dry-run) operation, not an actual deletion, which is useful. However, it does not disclose what the preview returns (e.g., affected records, confirmation) or any permissions needed. With no annotations, the description carries the burden and is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence. It is appropriately concise but could be expanded slightly (e.g., indicating what the preview shows) without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, the tool description is insufficient. It does not explain the behavior of the preview, the meaning of parameters, or how results are presented, leaving significant gaps for the agent to understand.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has four parameters with no descriptions (0% coverage). The tool description adds no information about what 'oid', 'agent', 'partition_key', or 'token_ttl_seconds' mean, leaving the agent to infer from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview deleting') and the specific resource ('entire ai_memory agent record'). It distinguishes from siblings like 'lc_preview_delete_ai_memory' by mentioning 'agent record'. However, it could be more precise about what 'preview' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'lc_preview_delete_ai_memory' or 'lc_get_ai_memory_record'. The sibling list includes similar preview delete tools, but the description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not explain what 'preview' entails (e.g., no side effects, requires confirmation, returns simulated result) or any safety implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, efficient but lacks necessary detail. It is not verbose, but could be more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description is too brief. It does not clarify the purpose of parameters, the nature of 'preview', or expected return value, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only mentions 'key hash' without explaining oid or token_ttl_seconds. No added value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview deleting), the resource (API key), and the method (by key hash). It distinguishes from siblings like lc_preview_create_api_key and lc_list_api_keys.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives, no prerequisites (e.g., need key hash from list), and no context on whether preview is a required step before actual deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies this is a preview (dry-run) via the word 'Preview', hinting it is non-destructive. However, without annotations, it does not explicitly state safety, required permissions, or side effects. It adds some behavioral context but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the action. It wastes no words, but some additional detail could be added without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain what the preview returns (e.g., confirmation token). It also leaves token_ttl_seconds unexplained. For a preview action, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The description does not explain any of the three parameters (oid, name, token_ttl_seconds) beyond their names. token_ttl_seconds is particularly unclear. This is insufficient for an agent to use correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (preview deleting) and the resource (integrity monitoring rule). It distinguishes from siblings like lc_preview_set_integrity_rule (which modifies) and lc_get_integrity_rule (reads). However, it could be more explicit about the preview nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, such as when to preview before actual deletion, or how it differs from other preview_delete_* tools. The description lacks context about prerequisites or next steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Preview deleting' implying a non-destructive dry-run, but it does not explain what the preview returns (e.g., summary of affected entities). With no annotations, the description should disclose behavioral traits like whether it is read-only or requires specific permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence, but it lacks essential details about parameters and behavior. It is front-loaded but too minimal to be fully effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, no annotation, and zero parameter descriptions, the description is incomplete. It does not explain the preview output, parameter semantics, or how this tool fits into the workflow of managing YARA rules.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has three parameters (oid, name, token_ttl_seconds) with no descriptions in the schema (0% coverage). The description adds no explanation of these parameters, leaving the agent without guidance on what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Preview deleting a YARA scanning rule' clearly identifies the action (preview delete) and the resource (YARA scanning rule). It distinguishes from siblings like 'lc_preview_delete_yara_source' (deletes a YARA source) and 'lc_preview_set_yara_rule' (sets a rule).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'lc_preview_delete_yara_source' or 'lc_preview_set_yara_rule'. There is no mention of prerequisites or context for using the preview delete action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behavioral traits. 'Preview isolating' suggests a dry-run, but it does not explain side effects, whether it modifies state, or what the output represents. The agent is left guessing about safety and perquisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and to the point, but it sacrifices necessary detail. It should be longer to include parameter hints and usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a preview action with 3 parameters and no output schema, the description is incomplete. It fails to explain what the preview does, what it returns, or how it differs from the actual isolation action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does not define 'oid', 'sensor_id', or 'token_ttl_seconds', leaving the agent unable to construct correct arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'preview isolating' and the resource 'sensor', distinguishing it from related tools like lc_preview_rejoin_sensor. It is explicit and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Given the many sibling preview tools, such as lc_preview_rejoin_sensor, the description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates it is a 'preview' (not the actual removal), but it does not disclose what the preview returns, whether it is read-only, required permissions, or any other behavioral traits beyond the obvious. With no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no redundancy. It is front-loaded but arguably too concise, sacrificing completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no annotations, no output schema, and sibling tools performing similar previews, the description is completely inadequate. It fails to explain the return value, how parameters relate, or when to use this over alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no information about the four parameters (oid, artifact_id, case_number, token_ttl_seconds). With 0% schema coverage, the agent must infer semantics solely from parameter names, which may be ambiguous (e.g., 'oid').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview removing'), the resource ('forensic artifact reference'), and the context ('from a case'). It effectively distinguishes this tool from siblings like lc_preview_remove_case_detection or lc_preview_remove_case_tags by specifying 'artifact reference'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this preview tool versus other actions, such as the actual removal or alternative previews. There is no mention of prerequisites, side effects, or conditions for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The word 'Preview' implies a dry-run, but the description does not explicitly state that no changes are made, what permissions are required, or any side effects. Without annotations, the description should provide more behavioral clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence), which is concise but at the expense of omitting critical information. It could be expanded slightly without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and multiple parameters, the description lacks context about what the preview returns, what 'sealing' entails, and how the preview result should be used. It is incomplete for effective tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the three parameters (oid, sensor_id, token_ttl_seconds). The agent receives no help understanding what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool previews sealing a sensor to prevent uninstall. It uses a specific verb-resource pairing ('Preview sealing') and distinguishes from sibling tools like lc_preview_unseal_sensor.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. For example, it doesn't mention that this is a dry-run before confirming, nor does it explain how to proceed after previewing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a preview (likely non-destructive) but does not disclose what the preview entails, whether it requires permissions, or any side effects. No annotations compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but perhaps too terse. It does not waste words, but more detail could be added without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and 4 parameters, the description is severely lacking. It does not explain what the preview returns, how to interpret results, or any operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaning for the 'enabled' parameter by mentioning 'toggling...enabled metadata'. However, the other three parameters (oid, name, token_ttl_seconds) are not explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Preview toggling' and the resource 'AI agent Hive record's enabled metadata'. It clearly indicates what the tool does and distinguishes it from siblings that perform actual set operations. However, the meaning of 'preview' is not elaborated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like the actual set operation or other preview tools. The description does not mention prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The term 'Preview' hints at a non-committal operation, but the description does not explicitly state that no changes are made, nor does it disclose any side effects, prerequisites, or permissions. Without annotations, the burden is on the description to be clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the tool's purpose. It is appropriately sized with no extraneous information, though it could benefit from additional structural elements like bullet points for parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (10 parameters, nested objects, no output schema), the description is too minimal. It does not explain the preview behavior, the meaning of the data object, or the return value, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should add meaning to the parameters but does not. It only mentions 'creating or updating a cloud adapter Hive record,' leaving the agent to infer parameter roles from names like oid, name, and data, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Preview creating or updating a cloud adapter Hive record,' which clearly identifies the tool's function as a dry-run for set operations. It differentiates from siblings like lc_get_cloud_adapter and lc_set_cloud_adapter by including 'Preview'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_set_cloud_adapter or other preview tools. The description fails to mention that this is a validation step and does not show when it is appropriate or when to use the actual set operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The term 'Preview' implies no actual modification, but the description does not explicitly state that the tool is a dry-run, what the return value contains, or that no changes are committed. No annotations exist to clarify behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) but lacks any structural detail such as parameter explanations or return value. It is not overly verbose, but could be improved by front-loading key behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 parameters with no schema coverage, no output schema, and no annotations, the description is severely incomplete. It does not explain the tool's return format, parameter roles, or any constraints, leaving the agent to guess.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 10 parameters (3 required), the description adds no meaning beyond parameter names. It does not explain what 'oid', 'data', 'name', etc. represent in the context of an SOP Hive record.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's verb ('Preview creating or updating') and resource ('SOP Hive record'). It distinguishes from sibling tools like lc_preview_set_hive_record and lc_preview_delete_sop.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_preview_set_hive_record or the actual set_sop tool. The description does not mention prerequisites or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It fails to state whether the preview is read-only, requires specific permissions, or returns validation results. The phrase 'preview updating' is ambiguous without explaining side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at 7 words, front-loaded. However, the brevity sacrifices necessary detail, making it borderline under-specified rather than efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no output schema, and no annotations, the description is highly incomplete. It does not explain what the preview returns, how to use the output, or the meaning of key fields like oid. An agent would lack essential context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description only mentions 'note or verdict', ignoring required parameters like oid, case_number, and entity_id, as well as token_ttl_seconds. It adds minimal value beyond the schema, leaving agents to infer parameter roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Preview updating a case entity note or verdict,' indicating the verb, resource, and aspects. Distinguishes from siblings like lc_preview_add_case_entity and lc_preview_remove_case_entity. However, it could be more explicit that 'preview' implies a dry run without committing changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusion criteria, or differentiate from similar preview tools for adding or removing case entities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only says 'Preview,' which suggests a dry run, but does not disclose what the preview entails (e.g., validation, estimation, results format). No details on side effects, permissions, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, achieving conciseness. However, given the tool has 5 parameters and no annotations, it is under-specified and lacks necessary detail, making it minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is incomplete for a tool with 5 parameters, no output schema, and no annotations. It does not explain what the preview returns, how to interpret results, or any prerequisites. Compared to sibling preview tools, it lacks context-specific details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and no parameter explanations in the description, the agent has no semantic information about parameters like oid, rule, sensor_id, timeout_seconds, or token_ttl_seconds. The description fails to add meaning beyond the schema's minimal definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Preview running an ad-hoc YARA scan on one sensor.' It uses specific verbs and nouns, and the name reinforces the purpose. It distinguishes from sibling preview tools that target different entities (cases, groups, etc.) and from other YARA-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., running a real scan, listing YARA rules) or prerequisites (e.g., sensor state, rule validity). There is no explicit 'when-to-use' or 'when-not-to-use' information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the action (estimate) but omits behavioral details like whether it is read-only, what happens on error, or any rate limits. The minimal description fails to disclose important traits beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence description is very concise and front-loaded with the key action, but it sacrifices completeness for brevity. For a tool with 5 parameters and no annotations, more substance is needed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the number of parameters, lack of output schema, and zero annotations, the description is incomplete. It does not specify return values, prerequisites, or how this tool fits among many sibling query tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning for 'start' and 'end' by mentioning 'unix-second time window', but leaves 'oid', 'query', and 'stream' unexplained. This partial compensation yields a score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies the action 'estimate an LCQL query' and the context 'against an explicit unix-second time window', clearly identifying the verb and resource. However, it does not differentiate from sibling tools like lc_validate_search_query or lc_execute_search_query, which could cause confusion despite the distinct 'estimate' focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Given the many sibling query-related tools (e.g., lc_execute_search_query, lc_validate_search_query, lc_poll_search_query), the absence of usage context makes it hard for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose any behavioral traits such as idempotency, required permissions, error handling (e.g., what happens if group_id is invalid), or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, concise and front-loaded. However, it sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity, the description lacks essential context such as what 'group definition' contains or how it relates to other group tools. The absence of output schema and parameter descriptions leaves the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'group_id' has no description in the schema (0% coverage). The tool description does not explain what the group_id represents or how to obtain it, relying solely on the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch') and the resource ('one organization group definition'). It distinguishes from sibling tool lc_list_groups which lists groups, and other group-related tools that modify groups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., lc_list_groups), no prerequisites, and no scenarios where it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the action. It does not disclose behavioral details such as authentication requirements, error handling for missing keys, or any rate limits. The word 'Fetch' implies read-only, but more context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words. However, it may be too terse and lacks any structure or additional information. It earns its place but could benefit from slight expansion.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description is very sparse. It tells the basic action but lacks details about return format, error scenarios, or prerequisites. For a simple get operation, it is minimally adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explain the parameters 'oid' and 'installation_key_id'. The description adds no meaning beyond the schema, which only provides names and types. The agent has no guidance on what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one installation key' clearly states the verb (Fetch) and the resource (one installation key). It distinguishes from sibling tools like lc_list_installation_keys, which lists all keys, by specifying 'one'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention that the oid and installation_key_id must be obtained from a list operation first, nor does it specify any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present. Description only says 'includes a signed download URL when returned' but does not disclose other behaviors such as authentication requirements, error conditions, or side effects (e.g., whether it creates logs).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with action and resource. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema and no annotations, the description provides basic purpose but lacks parameter semantics and usage context, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain what 'oid' or 'name' represent, leaving agents without any parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states verb 'Request' and resource 'payload API metadata', and mentions signed URL in output. However, it does not differentiate from sibling tools like lc_get_artifact_url or lc_list_payloads.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_get_artifact_url, or what prerequisites are needed (e.g., authentication). No exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the full burden. It only states 'Fetch details' without disclosing side effects, authentication needs, or what details are returned. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no waste. However, it could be slightly more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters, no output schema, and no annotations, the description is incomplete. It fails to clarify key aspects like the role of 'oid' or what 'include_enrichment' does.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters cve, oid, or include_enrichment. It adds no semantic value beyond the schema field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch details for one CVE' clearly states the verb (fetch) and resource (one CVE), and distinguishes it from sibling tools like lc_list_vulnerability_cves which list CVEs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as lc_list_vulnerability_cves. The description implies usage for a single CVE but lacks explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist. Description says 'fetch' implying read-only, but does not disclose any behavioral traits such as auth requirements, rate limits, or side effects. The burden is on description, which fails to provide transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb and object. No redundant information. However, it might be too concise given the need for parameter clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple (2 params, no output schema), but description lacks explanation of what the graph data contains, how 'oid' is used, and the effect of 'sort_asc'. Insufficient for the agent to understand the output or make informed choices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. Description does not explain the meaning of required parameter 'oid' or optional 'sort_asc'. With no additional context, the agent cannot understand how to use these parameters effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'fetch' and resource 'vulnerability dashboard graph data'. It distinguishes itself from sibling tools like lc_get_vulnerability_cve and lc_get_vulnerability_epss_history by specifying graph data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No exclusions, prerequisites, or conditions provided. Implicitly assumed to be for fetching graph data, but lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns one bounded page and requires a time window, which adds some behavioral context beyond the schema. However, it does not explain pagination behavior (e.g., how cursor works), ordering, rate limits, or what happens with no results. The description is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, which is efficient. However, it omits important details that could be added concisely, such as a note about pagination or filtering. It is under-specified for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 7 parameters, the description is incomplete. It does not explain pagination (cursor/limit), filtering capabilities, or the return structure. For a list tool, details like pagination behavior and response format are crucial. The description fails to provide sufficient context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The description only implies that 'start' and 'end' define a time window, but does not explain the format, meaning of 'oid', or how 'event_type' and 'sensor_id' filters work. It adds minimal semantic value beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists org audit logs with a bounded page for a time window. The verb 'list' and resource 'org audit logs' are specific, distinguishing it from sibling tools that list other resources like cases or sensors. However, the phrase 'bounded page' is somewhat vague and could be clarified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling list tools, the description does not specify that this is for audit logs or explain when not to use it. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description should disclose behavior beyond the simple listing. It does not mention read-only nature, pagination, filtering, or what 'linked' means. Insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, single sentence. No wasted words, but at the expense of necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With two required params, no output schema, and many sibling list tools, the description is too sparse. It does not explain what 'forensic artifacts' are, how parameters map, or response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds no meaning to the two required parameters ('oid', 'case_number'). Their purpose is entirely unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and resource 'forensic artifacts linked to a case', distinguishing it from siblings like lc_list_artifacts (general) and lc_list_case_detections (different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lc_list_artifacts, lc_list_case_entities). Does not specify prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states 'list... accessible', implying a read-only operation, but fails to disclose behaviors such as pagination (implied by limit parameter), ordering, rate limits, or what happens when no groups are found. The description is insufficient for an agent to understand the tool's runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 10 words, front-loaded with the core purpose. There is no extraneous information, earning a perfect score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the simplicity of the tool (one optional parameter, no output schema), the description is incomplete. It does not mention the return format (list of group objects), pagination behavior, or any limitations. An agent needs more context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'limit' has a default of 100 and no description in the schema (coverage 0%). The tool description does not explain its purpose or effect, leaving the agent to infer from the name. This adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists organization groups with a scope ('accessible to the authenticated identity'), distinguishing it from other list tools like lc_list_users or lc_list_orgs. The verb 'List' and resource 'organization groups' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_group (for a single group) or other list tools. There is no mention of prerequisites or context for when this tool should be invoked.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only says 'List', implying a read operation, but with no annotations provided, it fails to disclose any behavioral traits such as read-only nature, pagination, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is too brief and leaves out important details that would help an AI agent, given the lack of annotations and parameter descriptions in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters with no descriptions, no annotations, and no output schema. The description only covers the basic purpose and a hint of two parameters, leaving the return format and parameter semantics incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by linking 'oid' to 'for an org' and 'platform' to 'optionally filtered by platform', but it does not explain the 'limit' parameter or the format of platform values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'event schemas for an org', and mentions an optional platform filter. However, it does not differentiate from the sibling 'lc_get_schema' which likely retrieves a single schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool is used to list schemas for an org with an optional platform filter, but it does not provide explicit guidance on when to use this tool versus alternatives like 'lc_get_schema' or other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It discloses the preview behavior (no write), which is good, but omits details on required permissions, side effects, timeout behavior, or what parameters like ttl_seconds do.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) but at the expense of completeness. It omits parameter details and usage context, making it under-informative despite its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters and no output schema. The description does not cover return value, side effects, or parameter semantics, leaving the agent with insufficient information to correctly invoke the tool without external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds no information about any of the 5 parameters (oid, sensor_id, tag, ttl_seconds, token_ttl_seconds). The agent must guess parameter meanings from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it previews adding a tag to a sensor and emphasizes no write occurs until confirmation. It distinguishes this from other preview actions, but lacks detail on what the preview output is (e.g., success message or object).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is safe for testing (since it's a preview), but does not explicitly state when to use it versus alternatives like `lc_preview_remove_sensor_tag` or the non-preview version. No 'when not to use' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The tool name includes 'preview', which implies a dry-run with no side effects, and the description reiterates this. However, without annotations, the description should explicitly state that no actual creation or update occurs. No information is given about rate limits, authentication, or what happens if validation fails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It is front-loaded with the core action but omits context that would help an agent navigate the complex parameter set. The sentence earns its place by stating purpose, but the tool's complexity warrants more detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, no output schema, and no annotations, the description is severely incomplete. It doesn't explain what the preview returns (e.g., validation errors, preview of changes), how required parameters relate to existing lookups, or that only one data format should be specified at a time.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fails to explain any parameter meanings. For instance, it does not clarify that 'oid' likely identifies the lookup, 'name' its display name, or that yaml_content, newline_content, and lookup_data are alternative formats for the lookup data. The presence of token_ttl_seconds is also unaddressed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool previews creating or updating a lookup Hive record from a supported data format. It distinguishes from sibling tools like `lc_preview_set_hive_record` by specifying 'lookup', and from `lc_preview_set_lookup_enabled` by focusing on the record itself. However, it does not define what constitutes a supported data format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like `lc_set_lookup` or other preview_set tools, nor does it explain the relationship between the data format parameters (yaml_content, newline_content, lookup_data).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose side effects, permissions required, or data volume. It implies a read-only review but lacks explicit behavioral details that would be necessary given zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with 15 words, front-loading the action and scope. Efficient, but could benefit from a brief note on parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a broad review tool, the description omits return format, parameter details, and usage context. With no output schema and high parameter count, the description is inadequate for correct agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the 4 parameters (oid, start, end, limit). Schema coverage is 0%, so the agent gets no parameter meaning from either source. This severely hinders correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it reviews org posture across multiple specific areas: fleet, outputs, access, content, cases, and optional detection noise. This differentiates it from sibling tools like lc_review_fleet_health or lc_review_detection_noise, which focus on single aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It does not state prerequisites, when to prefer this over more focused review tools, or what to do with the results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It does not state that the tool is read-only, what it returns (e.g., boolean or error), or any behavioral traits. Very little transparency beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence of 6 words, which is efficient. However, it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 parameter, no output schema), the description lacks crucial details like what the output is (e.g., 'returns true if available') or any error conditions. The agent would need more context to use it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the one parameter 'name'. The description does not elaborate on the parameter format, constraints, or examples. It adds minimal value beyond stating that the tool checks a name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check') and the resource ('whether an organization name is available'). It is specific and distinguishes this tool from the many get_* and list_* siblings, as there is no other check tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It is a standalone sentence without any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must cover behavioral traits. It only says 'Fetch', implying a read operation, but does not disclose whether it is read-only, if authentication is needed, if it returns a large payload, or any side effects. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It conveys the core purpose efficiently, though it is quite short.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters, no output schema, and no annotations. The description does not explain what 'bounded' means precisely, the format of session_id or oid, what the history contains, or what the return value looks like. This is inadequate for an AI agent to use the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description must explain parameters. It only mentions 'bounded' vaguely, which could relate to the limit parameter, but does not explain oid or session_id at all. This adds negligible value over the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch', the resource 'conversation history', and the scope 'for one org-scoped AI session'. It distinguishes itself from sibling tools like lc_get_ai_agent or lc_list_ai_sessions by specifying exactly what it retrieves.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives such as lc_get_ai_memory or lc_list_ai_sessions. The description does not state prerequisites, context, or situations where it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Fetch' (implying read-only) but does not disclose error behavior (e.g., rule not found), return format, or whether namespace is optional. Minimal behavioral insight beyond the action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is front-loaded and concise. However, it is so brief that it omits important details, balancing conciseness against completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, annotations, or parameter descriptions, the description is insufficient. It does not explain the oid parameter, return value, or error cases. The tool is simple but still missing key context for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so parameters are undocumented. The description only clarifies 'name' and 'namespace' usage ('by name', 'from a hive namespace'), but the required 'oid' parameter is not explained. Missing meaning for oid significantly reduces semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetch') and resource ('D&R rule') and includes context ('by name from a hive namespace'). It clearly distinguishes from sibling 'list' tools (e.g., lc_list_dr_rules) by indicating single-rule retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like lc_list_dr_rules or other get tools (lc_get_fp_rule). The purpose is implied but not directly contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description bears full responsibility for disclosing behavior. It only states the operation without mentioning safety, permissions, or side effects. For a read-like tool, more context is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (5 words), which is concise but lacks structured information. It is not overly verbose, but could benefit from more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of output schema and annotations, the description is incomplete. It does not mention return values, error handling, or relationships to sibling tools like lc_list_sensor_events.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description does not explain parameters oid, sensor_id, or atom beyond the tool's title. The agent must infer meaning from context, adding minimal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one sensor event by atom' clearly states the action (fetch), the resource (sensor event), and the method (by atom). It distinguishes from sibling tools like lc_list_sensor_events by specifying 'one' and the key parameter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other tools such as lc_list_sensor_events. The description lacks context on prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Fetch' but does not disclose side effects, auth requirements, error handling, or safety profile. For a read operation, more context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise 5-word sentence, but it is overly minimal. It achieves conciseness at the expense of crucial details, making it less helpful for correct tool invocation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 required parameters, no output schema, and no annotations, the description is highly incomplete. It fails to explain what a Hive record is, how to obtain oid/name, or what the return value looks like, which is inadequate for a complex domain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description provides no explanation of the parameters oid and name. It does not clarify their roles, format, or whether both are required as a composite key. This leaves the agent without necessary context for parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches a single external adapter Hive record, with specific verb and resource. It distinguishes from siblings like lc_list_external_adapters (which lists multiple) and other get tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need a specific external adapter by oid and name, but it does not explicitly state when to use this tool versus alternatives like lc_list_external_adapters or other get tools. No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It states only the basic function but omits key details: whether it is read-only, error behavior if the record is missing, required permissions, or any side effects. The description is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, achieving high conciseness. It front-loads the action and resource. However, it may be excessively terse given the lack of supporting information in the schema or annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters, 3 required, no output schema, and no annotations. The description fails to explain what a 'Hive record' is, how the parameters identify the record, or what the function returns. Important contexts like return value format or error handling are absent, making the description incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description adds no explanation of the parameters. While names like oid, hive_name, key, and partition_key are somewhat self-explanatory, the description does not clarify their roles or how they should be used together, leaving the agent to infer from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one Hive record's data payload' clearly specifies the action (fetch), resource (Hive record), and scope (data payload). It distinguishes itself from sibling tools like lc_get_hive_record_metadata and lc_get_hive_schema, which retrieve different aspects of the same resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For instance, it does not explain that this tool retrieves the payload while lc_get_hive_record_metadata retrieves metadata, or mention any prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states 'fetch' which implies a read operation, but lacks details on authentication, rate limits, error behavior (e.g., not found), or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no superfluous content. However, it could be slightly expanded to include context about the purpose of the 'oid' parameter or the return value without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and only a one-sentence description, the tool definition is incomplete. An agent would lack understanding of what the 'oid' parameter represents, the format of the returned rule, and any potential errors or constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds minimal semantic value. It mentions fetching 'by name' but does not explain the 'oid' parameter (likely organization ID) or clarify that 'name' is the rule's name. The purpose of required parameters is largely implicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (fetch) and the resource (one integrity monitoring rule by name). It distinguishes itself from sibling tools like 'lc_list_integrity_rules' (which lists multiple) and 'lc_delete_integrity_rule' (which deletes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing to list rules first) or any context for when fetching a single rule is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states the function without mentioning read-only nature, authentication needs, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 6 words, very concise. However, it may be too brief given the lack of additional context, but it earns points for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet the description does not mention return format or structure. It also omits prerequisites, making it incomplete for an agent to fully understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description does not explain the 'oid' parameter beyond implying it's an organization ID. It adds minimal value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'organization inventory and quota metadata', distinguishing it from sibling tools like lc_get_org_stats or lc_get_org_note.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool over alternatives such as lc_get_quota_usage or other get tools. The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the action without disclosing side effects, permissions, or return details. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundancy, front-loaded. However, it may be too brief at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description should include more context such as the nature of URLs, read-only status, or error cases. It is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter oid with 0% description coverage. The description mentions 'explicit org' implying oid is the org ID, but adds no format, source, or constraints. Fails to compensate for schema lack.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'Fetch' and resource 'service URLs', and specifies scope 'for an explicit org'. It clearly distinguishes from siblings like lc_get_org_info which retrieves general org information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or when not to use. Among many lc_get_* siblings, this lacks differentiation cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only mentions listing with optional filters; lacks details on pagination, sorting, default behavior, or performance implications. For a list tool with 12 parameters, more behavioral context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with key information. It wastes no words, but could benefit from a brief expansion to cover usage guidance or parameter hints without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 12 parameters, no output schema, and no annotations, the description is incomplete. It mentions the required oid but ignores pagination (page_token), limit, sorting, and other filters. The agent lacks information about response format or pagination behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. The phrase 'with optional filters' is generic and does not explain any parameter's purpose, allowed values, or constraints. Parameter names (e.g., sort, order) are somewhat self-explanatory but no additional meaning is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List', the resource 'LimaCharlie cases', and the context 'for an explicit org, with optional filters'. It distinguishes from siblings like lc_get_case (singular) and lc_list_case_artifacts (different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lc_get_case, lc_search_case_entities, lc_review_case_backlog). No exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only mentions 'Fetch', implying a read operation. It does not disclose any constraints, side effects, pagination behavior, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence description is concise and front-loaded with the action, but it lacks additional structure such as parameter hints or examples, making it slightly too terse for a tool with four parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of parameter descriptions, output schema, and annotations, the description is incomplete. It does not cover how to use the parameters or what the response looks like, leaving significant gaps for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description adds no meaning to parameters like oid, atom, limit, or sensor_id, leaving the agent without guidance on what these parameters represent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'child events' with context 'for a parent event atom', making the tool's specific function distinct from siblings like lc_get_event or lc_list_sensor_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one has a parent event atom and needs its children, but it provides no explicit when-to-use, when-not-to-use, or alternatives, leaving the agent to infer context from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation ('List'), which is appropriate. However, with no annotations, it does not disclose any additional behavioral details like authentication requirements, rate limits, or whether the list is paginated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 parameter, list operation), the description is minimal but incomplete. It lacks details on what feedback channels are, the role of 'oid', and any limitations compared to sibling tools. No output schema is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one required parameter 'oid' with 0% description coverage. The description does not explain what 'oid' represents or how it affects the results, leaving the agent without crucial information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and the resource ('ext-feedback channel configuration'), distinguishing it from sibling list tools that focus on different resources. However, the term 'ext-feedback' may be ambiguous without domain knowledge.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as other list tools. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral info. It only states it does not download bytes but does not disclose permissions, rate limits, side effects, or return format. Minimal behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 10 words, highly concise but borderline under-specified. It is front-loaded with the key action, but could include more useful details without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters, no output schema, and no annotations, the description is insufficient. It does not describe what metadata includes, ordering, pagination, or how it differentiates from many sibling list tools. Lacks completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description does not explain the parameters (oid, limit) beyond their schema definitions. It adds no meaning to the parameters, failing to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists payload metadata without downloading bytes, using specific verb 'List' and resource 'payloads', and differentiates from other payload tools by noting the no-download aspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when only metadata is needed, but it does not explicitly state when to use this tool versus alternatives like lc_get_payload_download_url. No when-not or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose behavioral traits (e.g., read-only, required permissions, data scope). Only implies listing action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise but lacks detail. Could include parameter info without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no parameter descriptions, and sibling tools not differentiated. Description inadequate for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and description does not explain any parameter (oid, days, severities). No meaning added beyond field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists daily open-finding counts for vulnerability burndown views, specific verb+resource+context, distinguishing it from other list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The purpose implies it's for trending, but lacks alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It says 'Preview deleting' but does not explain what the preview entails—whether it modifies state, checks permissions, returns a confirmation, etc. The behavioral traits are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one phrase). While concise, it lacks necessary detail. It is not overly verbose but under-specifies, so it earns an average score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations, output schema, and parameter descriptions, the tool definition is incomplete. The description does not cover the context of what the preview outputs, error conditions, or prerequisites. More comprehensive information is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about the parameters. 'oid', 'name', and 'token_ttl_seconds' are left unexplained. The description does not help the agent understand which parameters are essential or how they relate to the operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Preview deleting') and the target resource ('a secret Hive record'). This distinguishes it from sibling tools like 'lc_preview_delete_hive_record' (generic) and 'lc_get_secret' (read-only). The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that this is a dry-run simulation and that actual deletion should be performed by a different tool (e.g., lc_delete_secret).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states 'Preview' implying no actual creation/update, but does not disclose what the preview returns, side effects, or that the result is likely a token for 'lc_confirm_action'. Minimal behavioral information beyond the verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks necessary detail. While it front-loads the purpose, it could benefit from a brief note on parameter usage or output. Adequate for a preview tool, but borderline under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no annotations, and no output schema, the description is incomplete. It does not explain the preview result (likely a token), how to use it (via lc_confirm_action), or any constraints. Users would need external knowledge to effectively use this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds no explanation for the 6 parameters (e.g., oid, name, patterns, tags, platforms, token_ttl_seconds). Users must infer meaning from names alone, which is insufficient for many parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it previews creating or updating an integrity monitoring rule, with specific verb 'Preview' and resource 'integrity monitoring rule'. This distinguishes it from sibling tools like 'lc_set_integrity_rule' (actual mutation) and 'lc_get_integrity_rule' (retrieval).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like 'lc_set_integrity_rule' or 'lc_confirm_action'. The description does not explain that previewing is for validation before committing, nor does it mention any prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a non-destructive action ('preview') but does not explicitly state that it is read-only or safe. With no annotations provided, the description should carry the burden of disclosure; it adds value by indicating the preview nature but lacks details on side effects or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it lacks necessary structural elements such as parameter explanations or usage context, making it minimally adequate. While not verbose, it sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the relationship between parameters, the nature of the preview result, or how to interpret the output. Critical context for safe and effective use is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description adds no information about the four parameters (oid, email, role, token_ttl_seconds). It does not explain what 'oid' represents, valid formats for 'email', acceptable 'role' values, or the purpose of 'token_ttl_seconds'. The description fails to compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: previewing a user's permissions replacement with a predefined role. It uses a specific verb ('preview') and identifies the resource (user permissions and role), which distinctively separates it from sibling tools like 'lc_preview_add_user_permission' or 'lc_preview_remove_user_permission'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Among many sibling tools dealing with permissions and roles, there is no mention of appropriate contexts or exclusions, leaving the agent to infer usage without support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description lacks behavioral details such as read-only nature, required permissions, rate limits, or side effects. The verb 'Summarize' implies a read operation but is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, brief sentence with no redundant information. However, it could benefit from slightly more context without becoming verbose, so it's not a perfect 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 2 parameters and no output schema or annotations, the description is insufficient for an agent to confidently use the tool. It lacks details on input constraints, return format, and operational context, making it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (no parameter descriptions). The description does not explain what 'oid' refers to (e.g., organization ID) or how 'limit' affects results. The tool's functionality is only broadly outlined, leaving parameter semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Summarize' and clearly defines the resource scope: users, permissions, groups, and API-key hygiene evidence. This distinguishes it from sibling review tools that cover different domains (e.g., case backlog, content coverage).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The sibling tools include several other review functions, but the description offers no criteria for selection or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses a 'force' action using API-key credentials but omits side effects like token invalidation, rate limits, or whether it's destructive. Minimal beyond the action itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no redundancy. Efficient but could add parameter details without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and only one parameter, the description is too brief. It does not explain what happens after refresh (e.g., new token, side effects), leaving gaps for a mutation-like operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter (oid) with 0% schema description coverage. The description does not explain this parameter at all, leaving the agent without guidance on its meaning or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Force' and clearly identifies the resource 'LimaCharlie JWT refresh'. It distinguishes from sibling tools like lc_auth_status (status) and lc_auth_whoami (whoami) by focusing on refresh action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a JWT refresh is needed but does not explicitly state when to use versus alternatives. No exclusions or direct comparison provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It mentions paginated behavior and bounded polling, but fails to disclose important traits such as whether the search is asynchronous, if it blocks, rate limits, validity of query_id, or any side effects. The description is too sparse for a tool with this complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the main action and output. It is efficient with no wasted words, though it could benefit from additional detail without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no output schema, no annotations, and many sibling tools, the description is incomplete. It lacks parameter explanations, return value format, and usage context necessary for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 5 parameters with 0% description coverage, yet the description provides no explanation of any parameter (e.g., what 'oid' represents, format of 'query', meaning of 'start' and 'end'). It fails to add any meaning beyond the schema, leaving the agent to guess.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it starts a paginated LCQL search and returns a query_id for bounded polling. The verb 'start' and resource 'LCQL search' are specific, and the mention of 'paginated' and 'bounded polling' distinguishes it from siblings like lc_execute_saved_query (which executes a saved query) and lc_poll_search_query (which polls results).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for starting paginated searches meant for bounded polling, but it does not explicitly state when to use this tool versus alternatives like lc_estimate_search_query or lc_execute_saved_query. It lacks explicit 'when to use' or 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it lacks details such as whether the operation is read-only, requires specific permissions, or has pagination. The description is too brief to convey important behavioral traits beyond the basic listing action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that conveys the main purpose without unnecessary words. It is appropriately sized for a simple list operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 parameters, no output schema), the description should provide more context about the response format, pagination behavior, and the meaning of 'oid'. The current description leaves important gaps for the agent to understand how to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any parameters. The schema shows 'oid' (required) and 'limit' (default 100), but their meanings are not provided. The description fails to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action ('List'), the resource ('API key identities'), and the context ('with AI-session usage data'). It distinguishes from siblings like lc_list_api_keys (which lists API keys without usage data) and lc_get_ai_usage (which might focus on specific usage).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for listing API key identities that have AI-session usage data, but it does not explicitly state when to use it versus alternatives like lc_list_api_keys or lc_get_ai_usage. No exclusion criteria or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the preview nature and that no write occurs until confirmation, but it does not describe side effects, required permissions, rate limits, or what happens after confirmation. Minimal behavioral information is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose and a key behavior. It is concise and front-loaded. However, it omits important details such as parameter explanations, which could be added without significant bloat. Still, it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no output schema, no annotations, and lacks parameter descriptions, the description is incomplete. It does not explain how to use the preview, what the output indicates, or how to proceed with confirmation. Significant gaps remain for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters (oid, tag, sensor_id, token_ttl_seconds) with 0% schema description coverage. The tool description does not explain any parameter's purpose, format, or constraints. The agent must rely solely on parameter names, which may be ambiguous (e.g., token_ttl_seconds). This is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Preview removing a tag from one sensor,' specifying the action (remove) and resource (tag on sensor). It distinguishes from sibling tools like lc_preview_add_sensor_tag by specifying 'remove' versus 'add.' The additional note 'No LimaCharlie write occurs until confirmation' clarifies that this is a preview only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for previewing tag removal before committing, but it does not explicitly state when to use this tool versus alternatives. No alternatives (e.g., a direct remove tool or confirmation step) are mentioned. The guidance is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the action without mentioning side effects, permissions, rate limits, or whether it is read-only. This is insufficient for an agent to understand the tool's implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose. It is front-loaded and has no fluff, though it could include more informative details without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with one parameter and no output schema, the description is minimally adequate but does not specify what the billing status includes or what the response format is. Gaps remain, especially for an agent unfamiliar with the API.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'oid' has no description in the schema (0% coverage) and the tool description does not explain its meaning, format, or examples. The description adds no value beyond the parameter type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch', the resource 'billing status', and the scope 'for an org', distinguishing it from sibling tools like lc_get_billing_details and lc_get_billing_invoice_url.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, when not to use it, or any prerequisites. The description lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Fetch' (presumably read-only) but does not confirm this, nor does it disclose permissions, rate limits, or response behavior. This is insufficient for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very brief and front-loaded, but it is arguably under-specified. While concise, it sacrifices necessary detail. A slightly longer description with parameter context would be more beneficial without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two required parameters, no output schema), the description is not complete. It does not explain what the response contains, possible errors, or permissions required. The agent would need additional context to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description does not add meaningful explanations for the parameters. It mentions 'by sensor ID' and 'for an explicit org' which loosely correspond to sensor_id and oid, but provides no format, constraints, or examples. The description only partially compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch', the resource 'one sensor by sensor ID', and the scope 'for an explicit org'. It effectively distinguishes from sibling tools like lc_list_sensors (returns multiple sensors) and lc_find_sensors_by_hostname (searches by hostname).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a specific sensor ID and org ID, but does not explicitly state when to use or not use this tool versus alternatives. No contrasting guidance with sibling tools like lc_get_sensor_isolation_status or lc_get_sensor_seal_status is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It states 'Fetch' (a read operation) but does not disclose behaviors such as error handling (e.g., when source not found), authorization requirements, or rate limits. This is insufficient for a tool with no structured behavioral hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) and front-loaded with the action and resource. While concise, it may be too terse, but for a simple fetch tool this is efficient and contains no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and two required parameters, the description could be more complete by hinting at the return structure or the relationship between oid and name. However, for a basic getter, the current minimalism is borderline adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, description must compensate. The description implies 'name' is the key identifier but does not explain the 'oid' parameter's role or why it is required. The agent lacks semantic context for half the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch one YARA source by name' uses a specific verb ('fetch'), identifies the resource ('YARA source'), and specifies the retrieval key ('by name'). It clearly distinguishes from sibling tools like lc_list_yara_sources which return multiple sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., lc_list_yara_sources). The description does not mention context, prerequisites, or scenarios where this specific fetch is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only says 'list' without revealing if it's read-only, requires auth, or any side effects. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no filler, front-loaded with verb and resource. Efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Minimal but sufficient for a parameterless list tool without output schema. However, workflow context (preview then confirm) and output nature are unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, schema coverage 100%, so description adds nothing about parameters. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states it lists action previews that are pending confirmation, distinguishing it from other list tools. However, 'local' is ambiguous and could be clarified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lc_confirm_action or other list tools. Missing context about the preview-confirm workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It states no task is queued, which is a key behavior, but lacks details on what the preview returns, side effects, or whether it checks feasibility. This is insufficient for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is direct and contains no unnecessary words. It efficiently communicates the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no output schema, and no annotations, the description is far too sparse. It fails to explain the preview process, the meaning of parameters, or what the user should do after preview, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation for any of the 5 parameters (oid, sensor_id, tasks, investigation_id, token_ttl_seconds). The description does not compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states it previews tasking one sensor and explicitly mentions that no task is queued until confirmation. This clearly identifies the tool's purpose and distinguishes it from actual tasking tools among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that after preview, confirmation is needed, but it does not explicitly name the confirm_action tool or provide when-to-use guidance compared to other preview tools or direct tasking.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description discloses the key behavioral trait that no detections are created (non-destructive), but lacks details on permissions, side effects, or output. Adequate for a dry-run but could expand.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 9 words, no filler. Front-loaded with action and key constraint. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 12 parameters, no output schema, and no annotations, the description is far too minimal. It fails to explain how to use parameters, what the output looks like, or what prerequisites exist. Incomplete for the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description adds no meaning to any of the 12 parameters. Terms like 'oid', 'start', 'end' remain unexplained. Agent cannot infer parameter purpose from description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs a dry-run of a D&R rule against historical data and explicitly notes that it does not create detections. This distinguishes it from siblings like lc_validate_replay_rule and lc_replay_scan_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or when not to use it. Agent must infer from name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral info. It only states 'Fetch', offering no details on authentication, rate limits, error responses, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no unnecessary words. However, it is too sparse to fully inform the agent, sacrificing completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and only a one-sentence description, the tool definition lacks context on return values, error conditions, or data format. The description is insufficient for a 2-parameter fetch operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two required parameters ('oid', 'session_id') with 0% description coverage. The description adds no meaning about these parameters, leaving the agent to infer their purpose from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb 'Fetch' and resource 'one org-scoped AI session'. It directly distinguishes from sibling tool 'lc_list_ai_sessions' which lists multiple sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (to fetch a single session), but provides no explicit guidance on when not to use it or alternatives such as lc_get_ai_session_history.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It implies a read operation ('fetch') but does not disclose required parameters (oid, name), error handling for non-existent rules, or confirm it is non-destructive. Minimal behavioral information beyond the verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at one sentence with no extraneous words. Front-loaded with the core purpose. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with no output schema, the description is adequate but lacks mention of what the tool returns (e.g., the rule object). Given the tool's simplicity and the presence of many sibling getters, it meets minimum viability but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It clarifies that 'name' is the rule name for fetching, but 'oid' (likely object/org ID) is left unexplained. Both parameters are required yet only one is addressed, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Fetch one false-positive rule by name', specifying verb (fetch), resource (false-positive rule), and retrieval method (by name). Among siblings like lc_list_fp_rules and lc_preview_set_fp_rule, this distinguishes it as a targeted lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as lc_list_fp_rules for listing all rules or lc_preview_set_fp_rule for creating/updating. The description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It fails to disclose behavioral traits such as pagination (despite a 'limit' parameter), required permissions, rate limits, or whether results are ordered. The description is too minimal to be transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single 6-word sentence is concise. However, it could be made slightly more informative without losing conciseness. Front-loading is adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple list operation with 2 parameters and no output schema. The description is minimal but sufficient for a basic understanding. However, it could include details about pagination, field descriptions, or relationship to extensions for better completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no parameter descriptions), so the description must compensate. It adds context by implying 'oid' is the org ID, but does not explain the 'limit' parameter or the format of 'oid'. Baseline with 0% coverage is higher (4), but minimal addition keeps it at 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List extension subscriptions') and the scope ('for an org'). It is specific and distinguishes from siblings like 'lc_list_available_extensions' (list available extensions, not subscriptions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., list_available_extensions, list_groups). No prerequisites, exclusions, or contextual hints are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states 'list,' implying a read-only operation, but lacks details on authentication requirements, rate limits, response structure, or any side effects. This is minimal disclosure for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is appropriately front-loaded. However, it could benefit from a brief note on the output (e.g., 'returns a list of strings'). Still, it is efficient and understandable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is largely complete. It tells the agent what the tool does. However, for completeness, mentioning that it requires no input and returns names would be ideal, but current version is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the schema coverage is 100% by default. The description adds no parameter info but also doesn't need to. Baseline for zero-parameter tools is 4, as the description is sufficient in this context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists 'known LimaCharlie hive type names,' using a specific verb and resource. It distinguishes from sibling tools like lc_get_hive_schema or lc_list_hive_records by specifying 'type names,' though could be more explicit about the output format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like lc_get_hive_schema or lc_list_hive_records. The description does not mention context, prerequisites, or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral aspects. It only states the basic action (list online sensors) with no mention of permissions, side effects, pagination, or what happens with invalid org IDs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence of 10 words, efficiently capturing the core function. However, it could be slightly more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters and no output schema, the description is incomplete. It fails to explain output format, how to get counts vs lists, pagination, or error handling, leaving significant gaps for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds little beyond the schema. It implicitly explains oid (explicit org) but omits the limit parameter entirely, not clarifying whether it controls list size or triggers count mode.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'currently online sensors' or 'online sensor counts', specifying it is for an explicit org. This distinguishes it from sibling tools like lc_list_sensors and other list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by requiring an explicit org (oid is required), but does not explicitly state when to use this tool versus alternatives like lc_list_sensors, nor does it provide any when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions 'one bounded page' hinting at pagination but does not explain sorting, rate limits, or if the operation is read-only. The behavioral profile is insufficient for safe agent invocation without additional context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that conveys the core functionality without any redundant word or phrase. Every word adds meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters, no output schema, and no annotations, the description is too brief to be fully complete. It does not explain pagination mechanics, filtering by category, or the structure of the returned results, leaving significant gaps for an agent to operate correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must clarify parameters. It explains that 'oid' is the org, 'start' and 'end' define the time window, but it omits the optional parameters 'limit', 'cursor', and 'category', leaving their purpose unclear. The description adds value for the required parameters but fails to cover the full schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'detections', and essential constraints: 'one bounded page', 'explicit org', and 'unix-second time window'. This distinguishes it from related tools like lc_get_detection (single) and lc_list_case_detections (scoped to a case).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (need an org and time window) but provides no guidance on when to use this tool versus alternatives like lc_get_detection or lc_list_case_detections. There are no explicit exclusions or usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states that the tool lists audit logs; it does not mention read-only nature, pagination, ordering, time range, or any side effects. For a simple list operation, this is minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 9 words, front-loading the action and resource. It is highly concise with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters and no output schema or annotations, the description is incomplete. It does not explain the optional limit parameter, describe the return format, or mention any constraints like pagination. More details are needed for an agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description must add meaning. It hints that group_id identifies the group, but does not explain the limit parameter or its default value. The context of 'for one organization group' provides only slight value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List', the resource 'audit logs', and the scope 'for one organization group'. This specificity distinguishes it from sibling tools like lc_list_audit_logs (which likely lists all audit logs) and lc_list_groups (which lists groups).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that a group_id is needed but does not provide explicit guidance on when to use this tool versus alternatives such as lc_list_audit_logs or lc_list_groups. There is no mention of prerequisites, optimal scenarios, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It only states 'List service jobs', which suggests a read operation, but misses details like pagination, ordering, limits, or response format. This is insufficient for a list tool with 5 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 9 words, front-loading the core action and constraints. Every word contributes value, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters (3 required), no output schema, and no annotations, the description lacks completeness. It does not cover pagination, result structure, error conditions, or operational nuances essential for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It clarifies that oid is an org ID and start/end define a time window, but does not explain units (e.g., epoch timestamps) or the purpose of limit and sensor_id, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'service jobs', with explicit constraints for an org and time window. This distinguishes it from other list tools among siblings by specifying the exact resource and required context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for listing jobs with a specific org and time range, but it does not provide explicit guidance on when to use versus alternatives (e.g., lc_get_job for a single job) or conditions to avoid misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the important safety note that secret values are not exposed. However, no annotations are provided, and the description lacks other behavioral details such as pagination, ordering, or auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (8 words) and front-loads the key action and constraint. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero schema coverage and no annotations, the description is too brief. It omits parameter explanations and usage context, leaving significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description provides no explanation for the 'oid' and 'limit' parameters. Schema description coverage is 0%, and the description fails to add meaning beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list), the resource (secret Hive records), and a key constraint (without exposing secret values). It distinguishes from related tools like lc_get_secret which would expose values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives are mentioned. From sibling names, it's implied that lc_get_secret is for retrieving values, but this is not stated directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It declares the tool will describe 'inputs, bounds, side effects, and use cases', which is transparent about expected output. However, it does not disclose any potential side effects, authentication requirements, or limitations (e.g., whether it requires an active session).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the verb. However, it could be slightly more structured (e.g., bullet points for the aspects described).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the meta-tool nature and absence of output schema, the description is reasonably complete in stating what it covers (inputs, bounds, side effects, use cases). However, it lacks details on output format, whether it lists all tools or filtered by profile, and how the optional parameter affects behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional parameter 'profile' with no description, and the tool description does not explain its meaning or usage. With 0% schema description coverage, the description should compensate but fails to add any value regarding the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Describe LimaCharlie MCP tools, inputs, bounds, side effects, and use cases.' It specifies the verb 'Describe' and the resource 'LimaCharlie MCP tools', distinguishing it from sibling tools which are actual operational tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining descriptions of tools, but does not explicitly state when to use it versus alternatives or provide any exclusions. The sibling list contains many other tools, but no guidance is given on when to invoke this meta-tool instead of directly using other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It only states 'Validate LCQL through the org search service' with no disclosure of side effects, authentication needs, rate limits, or return format. More behavioral context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that delivers the core purpose efficiently. It is front-loaded and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and 5 parameters, the description is insufficient. It does not explain what validation entails, expected output, or constraints, making it hard for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain any of the 5 parameters (oid, query, start, end, stream). It adds no meaning beyond the schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate LCQL through the org search service before estimation or execution' clearly states the tool's verb (validate) and resource (LCQL), and distinguishes it from related siblings like lc_estimate_search_query and lc_execute_search_query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this tool 'before estimation or execution', providing context. It does not list alternatives or when not to use, but the purpose is clear enough for an agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool polls repeatedly and has a bounded timeout, which is useful. However, it does not define 'terminal state', specify behavior on timeout, or mention side effects. With no annotations, the description carries the full burden, but it leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 10 words, front-loaded with the verb 'Poll'. Every word is necessary and contributes to clarity, with zero wasted space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple polling tool with no output schema and no annotations, the description lacks crucial details: what the return value is on terminal state versus timeout, the significance of required parameters oid and job_id, and how the polling mechanism behaves. This leaves the agent underinformed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about the four parameters (oid, job_id, timeout_seconds, poll_interval_seconds). The parameter names are self-explanatory, but the description fails to add any value beyond the schema's type definitions, leaving the agent without guidance on usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'poll', the resource 'one service job', and the condition 'until terminal state or bounded timeout'. It effectively distinguishes the tool from siblings like lc_get_job (which returns current state) and lc_poll_search_query (which polls queries).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'poll one service job' implies it is used to wait for a job to complete, but it does not explicitly state when to use this tool versus alternatives like lc_get_job or lc_list_jobs. No exclusions or alternatives are mentioned, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions two modes (identity only vs. permission test) but does not explain what happens in each mode, return format, side effects, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no unnecessary words. It front-loads the primary purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two optional parameters and no output schema, the description covers the core purpose but lacks details about return values and the distinction between parameterless vs. parameterized calls.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the joint use of oid and check_perm for testing permissions but does not define individual parameters (e.g., what oid represents or the expected format of check_perm), leaving significant ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the authenticated LimaCharlie API identity, using a specific verb and resource. It also explains an additional capability (testing permissions), which distinguishes it from sibling auth tools like lc_auth_refresh and lc_auth_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by saying 'Pass both oid and check_perm to test a specific permission', but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or usage scenarios for without parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It only states what it does, but not side effects, auth needs, or data scope beyond 'explicit org'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with no output schema, description covers what and how. Lacks details about return format or any constraints, but adequate for minimal tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description mentions 'by detection ID for an explicit org' giving context for both parameters, but schema coverage is 0% and no detailed parameter descriptions are added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Fetch' and resource 'detection' with specific criteria (by detection ID for explicit org). Distinguishes from siblings like lc_list_detections which fetches multiple.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., lc_list_detections). Lacks context for best use or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description suggests a preview (non-destructive) operation through the term 'Preview', but it does not explicitly confirm that no changes are made or describe the output format. It fails to disclose permissions or side effects, relying on the tool name to imply safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. However, it is under-specified given the tool's complexity and missing details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and 0% parameter documentation, the description fails to provide sufficient context. Key aspects like return values, preview behavior, and parameter roles are absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description only adds meaning to the 'tags' parameter ('replacing the exact remaining tag list'). Parameters oid, case_number, and token_ttl_seconds remain unexplained, leaving the agent to infer from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Preview removing tags from a case by replacing the exact remaining tag list.' It uses specific verb and resource, and the mechanism distinguishes it from siblings like lc_preview_add_case_tags and lc_preview_set_case_tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies this is for previewing removal by specifying the new tag list, but it does not contrast with alternatives or state prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It minimally indicates a read operation ('fetch') and mentions a scope parameter, but does not explain default behavior, side effects, rate limits, or output format. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 15 words, conveying essential information without any fluff. It is optimally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, no annotations, and two parameters with zero description, the description is minimal. It tells what the tool does but lacks details about output, pagination, and the effect of limit. For a simple tool, it is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains that oid is used as an org-key JWT scope, adding meaning beyond the schema. However, it does not explain the limit parameter (integer, default 100) at all, so partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch') and the resource ('LimaCharlie ontology/event definitions'). It also mentions the optional use of oid as a JWT scope, which distinguishes it from other 'get' tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is given. The description implies usage for retrieving ontology definitions, but no alternatives are mentioned. The mention of oid scope gives a hint about authentication but is not a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description partially compensates by noting sensitive fields are redacted, which is a key behavioral trait. However, it lacks information about authentication requirements, side effects, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no waste. It conveys the core purpose and a key behavioral detail efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and 0% schema coverage, the description leaves significant gaps. It does not explain what a secret Hive record is, what fields are redacted, or the meaning of the two required parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the two required parameters (oid, name). It only states the tool fetches a secret record, leaving the agent to infer parameter meanings from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches one secret Hive record with sensitive fields redacted. The verb 'Fetch' and resource 'secret Hive record' are specific, and the detail about redaction distinguishes it from generic get tools like lc_get_hive_record or list tools like lc_list_secrets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a single secret is needed but provides no explicit guidance on when to use this tool versus alternatives, no exclusions, and no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. However, it only states the action and parameters, omitting details such as pagination, ordering, return format, or side effects. This is minimal transparency for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the main action and key conditions. It is concisely written with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with 3 parameters, no output schema, and no annotations, the description provides the essential context (required org and optional filter). However, it lacks information on return value structure, pagination, or sorting, which would be important for an AI agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by associating 'for an explicit org' with the required 'oid' parameter and mentioning 'optionally filtered by selector' for the 'selector' parameter. It does not explain the 'limit' parameter. This partially compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('list'), resource ('sensors'), scope ('for an explicit org'), and an optional filter ('by selector'). It effectively distinguishes from sibling tools like lc_find_sensors_by_hostname or lc_list_online_sensors, providing a specific purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context (explicit org required, optional selector) but does not explicitly state when not to use this tool or provide alternatives. Given the large number of sibling list tools, a bit more guidance would be beneficial.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it polls and waits for online status with a bounded timeout, which covers basic behavior. However, it does not explain what happens on timeout (e.g., error or false return) or any side effects. With no annotations, it carries the full burden but only partially meets it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) and front-loads the action and resource. Every word is informative with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is too brief. It does not explain the return value, the effect of the polling parameters, or how the result is communicated. The agent lacks sufficient context to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to any of the 4 parameters. It does not explain oid, sensor_id, timeout_seconds, or poll_interval_seconds, leaving the agent to guess their roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action ('poll') and resource ('one sensor') with a specific condition ('until online or bounded timeout'). It distinguishes from siblings like lc_list_online_sensors and lc_get_sensor by focusing on waiting for a specific sensor to come online.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to wait for a sensor to be online, but does not explicitly provide guidance on when to use vs alternatives (e.g., lc_list_online_sensors or lc_get_sensor). No exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses that the operation is local and does not involve server calls. However, it does not detail expected behavior on invalid tokens, idempotency, or side effects. Basic transparency is provided but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no redundant words. The key information is front-loaded: 'Cancel one pending local action preview'. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one param, no output schema), the description covers the core action. However, it does not explain what a 'local action preview' is or that the token comes from a previous lc_preview_* call. Missing context that would help an agent correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It implies that 'confirmation_token' identifies the preview to cancel, adding meaning beyond the raw schema. But it omits detail about the token's origin (e.g., from a preview creation call), which would improve usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'cancel' and the resource 'pending local action preview'. It distinguishes from siblings like lc_confirm_action (which confirms) and lc_cancel_search_query (which cancels queries). The phrase 'without calling LimaCharlie' further differentiates this as a local-only cancellation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: cancel a preview that has been created locally. It says 'without calling LimaCharlie', hinting it's for local previews. However, it does not explicitly state when to use this versus lc_confirm_action or other cancel tools, nor does it mention prerequisites like having created a preview first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states 'Fetch' which implies a read-only operation. However, it does not disclose potential errors (e.g., case not found), permissions required, or rate limits. For a simple fetch, this may suffice, but more context would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-formed sentence with no redundant information. Every word adds value, making it highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 required params, no output schema), the description covers the essential purpose and inputs. It doesn't describe the return value, but for a straightforward get operation, this is often assumed. Could be slightly more complete by hinting at the response structure, but current level is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must add meaning. It mentions 'case number' and 'explicit org' corresponding to the two required parameters, oid and case_number. This clarifies their roles but lacks detail on format or validation. Baseline 3 is appropriate as it provides some semantics but not extensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Fetch', names the resource 'LimaCharlie case', and specifies the two key identifiers: case number and explicit org. This clearly distinguishes it from sibling tools like lc_list_cases (for listing) and other case-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It's implied that you use it when you have a specific case_number and need to retrieve that single case, but it doesn't contrast with similar tools or mention prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as pagination, sorting, or that it only returns orgs the API key has access to. It simply restates the action without additional context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and contains no unnecessary words. Every part contributes to the understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and no output schema, the description is adequate. However, it could mention any limitations like scope of orgs returned, but it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and the schema coverage is 100%. The description adds no parameter information, but since none are needed, a baseline score of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists organizations available to the authenticated LimaCharlie API key, using a specific verb and resource. Among many sibling list tools, it distinguishes itself by focusing on organizations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (list organizations for the authenticated key) but does not explicitly state when to use this tool over alternatives or mention exclusions. It provides no guidance on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It states 'No write is sent until confirmation', clearly indicating the non-destructive, preview-only behavior. However, it does not disclose the response format (e.g., return token) or authentication requirements. The lack of annotations is partially compensated by this explicit statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence: 'Preview updating a case. No write is sent until confirmation.' It is front-loaded with purpose and critical behavioral note. No extraneous information; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides core preview semantics but lacks guidance on the confirmation step (e.g., which tool to use to commit). With no output schema, agents are left to infer the return value. For a complex tool with many parameters, the description is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 10 parameters, the tool description adds no explanation of parameter meaning (e.g., what 'oid' or 'case_number' represent). The phrase 'Preview updating a case' implies parameters are update fields, but the agent must infer semantics from names alone. Minimal value added beyond the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'Preview updating a case', which clearly states the verb (preview) and resource (case update). It distinguishes from sibling tools like lc_get_case (read-only) and lc_preview_create_case (different operation). The behavior is uniquely identified among many preview tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for testing updates before committing, but it does not explicitly state when to use this tool versus alternatives like lc_get_case or lc_confirm_action. No exclusions or usage context beyond the preview nature is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that no binaries are downloaded, which is a key behavioral trait. However, it does not state authorization requirements, rate limits, or response behavior (e.g., empty list state).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is short and to the point. It front-loads the action and resource, with no wasted words. It earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description provides the essential purpose. However, it lacks details about the nature of the URLs (e.g., platform-specific, format) and any conditions. For a simple list tool, it is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema coverage is 100% (empty schema). The description adds no extra parameter info, which is appropriate since baseline is 4 for 0 parameters. It correctly describes the action without needing to detail parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List', the resource 'supported adapter binary target URLs', and the qualifier 'without downloading binaries', making the tool's purpose unambiguous. It distinguishes from sibling tools like lc_list_cloud_adapters which list adapters themselves.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (to get URLs without downloading), but provides no explicit guidance on alternatives or when not to use it. Given many list tools exist, some usage context would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the tool is a simple read operation with no side effects. The description adequately implies it returns a list of organizations accessible to the caller, which is sufficient for this straightforward tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence that directly states the tool's purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description does not mention what the returned data contains (e.g., IDs, names). For a simple listing tool, this is a minor gap. The tool is still usable but lacks full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so baseline score is 4 per guidelines. The description does not add parameter semantics as none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists 'ext-cases organizations accessible to the caller', using a specific verb and resource. It distinguishes from siblings like 'lc_list_orgs' by specifying 'ext-cases' and 'accessible to the caller'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'lc_list_orgs' or 'lc_get_org_info'. The description only states what it does, without any when-not or contextual cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly states the tool lists without downloading, making it clear it is a non-destructive read operation. However, it does not disclose whether the tool requires authentication or any other behavioral nuance, though for a zero-parameter list tool, this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose and constraint. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description is mostly sufficient. It clearly states what the tool lists. However, it could be enhanced by mentioning the output format (e.g., 'returns a list of URLs') or noting that it lists all available download targets.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so schema coverage is perfect at 100%. The description adds meaning by specifying what is being listed (sensor installer target URLs). There is no need to document parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists supported sensor installer target URLs without downloading binaries. It specifies the verb 'List', the resource 'supported sensor installer target URLs', and the constraint 'without downloading'. It distinguishes from siblings like lc_list_adapter_download_targets by focusing on sensors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for listing URLs only and not for downloading, but it does not explicitly state when to use this tool vs alternatives like lc_list_adapter_download_targets. No usage context or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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