Splunk MCP for SOC Operations

Server Quality Checklist

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Latest release: v0.3.0
Disambiguation2/5
Several tools have overlapping purposes or are direct aliases (search_splunk/run_splunk_query, health_check/health). Additionally, check_ioc_reputation and enrich_ip_with_threat_intel both perform IP reputation checks, and list_indexes/get_indexes_and_sourcetypes overlap, creating ambiguity in tool selection.
Naming Consistency4/5
Tool names follow a consistent snake_case verb_noun pattern (e.g., list_users, get_field_summary). Minor deviations include current_user (noun-first) and the alias pairs search_splunk/run_splunk_query and health_check/health, but these do not break the overall pattern.
Tool Count2/5
31 tools is heavily above the typical well-scoped range. While the broad SOC scope justifies many tools, the presence of duplicate/overlapping tools inflates the count and suggests consolidation would be beneficial.
Completeness3/5
The tool set covers a wide range of SOC operations including search, threat intel, analytics, incident response, and DeepTempo integration. However, missing update/delete capabilities for saved searches, users, incidents, and threat list entries leave lifecycles incomplete and create dead ends for incident management.
Average 4.1/5 across 31 of 31 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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 Apache 2.0.
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.
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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?
With no annotations, the description must disclose behavioral traits. It mentions the search execution and result return but does not explicitly state it is read-only, discuss auth/permissions, rate limits, or side effects. The default time descriptions ('24 hours ago' vs schema's '-24h') are slightly imprecise but not contradictory.
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 compact with clear headings for Args and Returns. It is efficiently structured but includes redundancy by restating parameter defaults that are in the schema, which slightly detracts from 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?
The output schema exists, so return values need not be explained. For a relatively simple search tool, the description covers the core function and parameters. However, missing usage guidance, no differentiation from siblings, and no mention of time format limitations leave notable gaps for a complete picture.
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 repeats parameter names and defaults already present in the schema but adds no deeper meaning, such as time format details, result size limits, or query syntax examples. The 'Args' section provides minimal interpretive 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 action ('Execute a Splunk search query') and the resource ('Splunk'), with a straightforward return of results. However, it does not differentiate from the sibling tool 'run_splunk_query', which likely serves a similar or identical 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?
No guidance is provided about when to use this tool versus alternatives like 'run_splunk_query' or other search-related tools. The description only states what it does, not the intended 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 are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the operation is read-only, requires authentication, or what failure semantics look like. It only states the basic function without any further detail.
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 filler. It directly states the two main outputs without unnecessary detail.
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 (0 parameters, output schema present), the description adequately covers the purpose and return scope. It could include usage guidance or behavioral notes, but those are captured in other dimensions. The description is sufficient for a basic health check tool.
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, and the input schema is empty, so the description needs to add no parameter information. The baseline for 0 params is 4, and the description does not need to compensate for any missing 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 uses specific verbs 'Get' and 'list' with clear resources: 'basic Splunk connection information' and 'available apps'. It clearly states what the tool does. However, it does not explicitly distinguish itself from siblings like 'health' or 'ping', which likely have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 exclusions, prerequisites, or relationships to sibling tools such as 'health', 'ping', or 'list_indexes'. There is no when-to-use context.
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?
Without annotations, the description carries the burden of behavioral transparency. It describes the operation as identifying rare events and specifies the return type, which implies a read-only function. However, it doesn't disclose the rarity calculation methodology, potential performance impacts, or edge-case behavior, leaving room for more 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?
The description is well-structured with an opening summary, Args, and Returns sections, and stays concise. The first two sentences are somewhat redundant, costing a point, but overall every section contributes value.
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 covers the tool's purpose, all parameters, and return value, and the presence of an output schema reduces the need for return details. However, it lacks usage guidance and differentiation from similar analysis tools, and without annotations there are no behavioral caveats.
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 Args section provides meaningful descriptions for all four parameters, including an example for field and a concrete percentage explanation for rarity_threshold. This fully compensates for the 0% schema description coverage, though the timeframe format could be more explicit.
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 opens with a clear verb and object: 'Identify statistically rare events' and adds threat relevance. It distinguishes itself from siblings like detect_anomalies by focusing specifically on rarity and new attack techniques, even though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 siblings like detect_anomalies or baseline_normal_behavior. The threat context implies a hunting use case, but there are no prerequisites, exclusions, or alternative tool recommendations.
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 mentions creating a behavioral profile and returning a dictionary, but does not disclose whether this operation writes to any store, requires specific permissions, or has side effects. For a security tool, this lack of behavioral detail 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with a clear one-sentence summary, followed by a purpose sentence, then concise Args and Returns sections. Every sentence earns its place with no unnecessary 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?
The description covers purpose and parameters well, and an output schema exists to explain return values. However, given the lack of annotations, it is incomplete regarding prerequisites (e.g., data availability, permissions) and behavioral traits (side effects, state changes). More context is needed for an agent to use it safely and correctly.
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?
With schema description coverage at 0%, the Args section in the description is essential. It explains each parameter's purpose (e.g., 'entity: Entity to profile', 'metrics: List of metrics to baseline') and notes defaults. This adds meaning beyond the raw schema, though some format details (like timeframe syntax) are left vague.
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 states 'Learn and establish normal behavior baseline for a user, host, or service' with a specific verb and resource, and further clarifies it creates a behavioral profile for detecting deviations. This clearly distinguishes it from sibling tools like detect_anomalies, which focus on detection rather than baseline creation.
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 to establish a baseline before detecting deviations or insider threats, but it does not explicitly mention when to use it versus alternatives like detect_anomalies or identify_rare_events. There is no exclusion guidance or named alternatives, only the implied context of baseline creation.
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 burden of behavioral disclosure. It states that the endpoint 'performs a search' and limits results to 'all accessible indexes,' which adds context about scope and execution. However, it does not mention performance implications, rate limits, or potential cost of the search, leaving some opacity.
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 well-structured with a clear opening statement, a bulleted list of gathered data, and a breakdown of the return dictionary. It earns its place without extraneous fluff, though the 'Returns' section could be more compact if it relied on the output schema.
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 zero-parameter tool with an output schema, the description covers purpose, behavior, and return structure sufficiently. It explains the search-based nature and the components of the returned dictionary. Minor gaps remain, such as whether a default time range exists or how 'accessible' is determined, but these are not critical for this simple tool.
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, and the input schema is empty. The baseline for zero params is 4, and the description correctly avoids inventing parameter details. It does not need to add parameter semantics because there are none to explain.
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 explicitly states 'Get a list of all indexes and their sourcetypes,' which is a specific verb+resource. It further details additional outputs (event counts, time range info), distinguishing it from sibling tools like list_indexes (which focuses only on indexes) and get_index_info (which targets a single index).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 notes 'This endpoint performs a search,' implying a heavier operation, but there is no explicit mention of whether to prefer this over list_indexes for index-only tasks or how to use it for broad discovery vs targeted queries.
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 the admin privilege requirement, which is a key behavioral trait. However, it does not explicitly state whether the operation is read-only or what happens if privileges are insufficient, leaving some 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 concise sentence, front-loaded with the action and resource. It contains no redundancy and each word adds value, making it highly concise and well-structured.
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) and the presence of an output schema, the description adequately states the operation and a necessary precondition. It could mention if it returns only a subset of fields or any limitations, but the output schema likely covers return details. Overall, it is complete for the tool's complexity.
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 the schema coverage is trivially 100%. With no parameters to describe, the baseline is 4. The description adds nothing beyond the parameterless nature, which is acceptable.
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 and resource: 'List all Splunk users'. This clearly defines the tool's function and distinguishes it from siblings like list_indexes or list_saved_searches, even without naming alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 only notes that admin privileges are required, which is a prerequisite rather than usage guidance. It does not specify when to prefer this tool over other search/query tools or any exclusions. No alternatives or context are 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 must carry the behavioral burden. It implies a read-only operation ('Get a list') and states the return type (dictionary), which is minimal but adequate for a simple read tool. It does not explicitly disclose auth requirements or whether 'available' implies permissions or configuration, but it doesn't mislead.
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: two short sentences that clearly state the purpose and return type. Every word earns its place, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter listing tool with an output schema, the description covers the essential information: what is listed and what the return structure is. It is complete for the tool's simplicity, though it could benefit from a usage note.
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 takes zero parameters, so the input schema is already empty. The baseline for 0 parameters is 4; no further parameter elaboration is needed.
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 ('Get a list') and resource ('all available Splunk indexes'), clearly distinguishing it from sibling tools like get_index_info or list_users. The scope 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 is provided on when to use this tool versus alternatives such as get_index_info or get_indexes_and_sourcetypes. The description merely states what it does without any contextual or exclusionary information.
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 states that the tool returns a dictionary with status and basic server information, including version and server time, implying a read-only behavior. However, it does not mention authentication, rate limits, side effects, or error behavior. For a simple ping this is adequate but not exhaustive.
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 succinct and well-structured: a lead sentence, a bulleted list of benefits, and a return-type note. Every sentence contributes value, with no fluff or repetition.
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 tool this simple, the description covers the purpose, usage, and return value. It omits details like error responses or authentication, but given the trivial nature of a ping endpoint, the provided information is largely sufficient. The lack of differentiation from sibling health tools slightly reduces completeness.
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, and the input schema is empty with full coverage. According to the guidelines, the baseline for zero parameters is 4. The description does not need to explain parameters that do not exist, and it adds no parameter-level detail because none is required.
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 a ping endpoint for checking server availability and retrieving basic server info (version, server time). The verbs 'check' and 'get' are specific, and the resource is well-defined. However, it does not differentiate from sibling health-check tools like 'health_check' or 'health', so it loses the top score.
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 frames the tool as a 'lightweight way' to verify server responsiveness and check connectivity without complex API calls, which gives clear context for when it should be used. It does not explicitly name alternatives or state when not to use it, so it does not achieve a 5.
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 of behavioral disclosure. It discloses that the operation is an upsert ('creates or updates'), describes the side effect of being used for detection, and specifies the return dictionary. However, it does not mention required permissions, reversibility, or what happens on failure or conflict.
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 well-structured with separate Args and Returns sections, making it easy to scan. However, there is slight redundancy (e.g., 'threat intelligence list' and 'threat intelligence entry in Splunk' in sequential sentences) that could be tightened.
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?
The description covers the tool's purpose, all parameters, and return values, which is sufficient for a moderately simple tool. It lacks explicit usage guidance versus alternatives and does not discuss operational prerequisites, but given the output schema and parameter descriptions, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates. Each parameter is explained with context: ioc_value examples (IP, domain, hash), ioc_type enumerated, threat_type classification ('malicious', 'suspicious', 'watchlist'), and expiration_days clarifies '0 = never'. This is more helpful than the bare 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 action: 'Add an IOC to Splunk's threat intelligence list.' It uses a specific verb ('Add') and resource ('Splunk's threat intelligence list'), distinguishing it from sibling tools like check_ioc_reputation or block_ip_address.
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 want to add or update a threat intelligence entry, noting it 'creates or updates' and is 'used for automated detection and correlation.' However, it does not explicitly mention when to use this tool versus alternatives, nor does it provide any exclusions 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?
No annotations are provided, so the description carries the burden. It discloses that it queries free threat intelligence sources and returns a dictionary with specific fields (reputation_score, is_malicious, etc.), adding useful context. However, it does not mention caveats like rate limits, network dependence, or whether any state is modified, so transparency is moderate.
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 opens with a clear one-sentence purpose statement, then provides structured Args and Returns sections. It is somewhat longer due to the return field list, but each sentence adds value. Given that an output schema exists, the Returns section is somewhat redundant, but the overall structure is clean and front-loaded.
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 tool with only 2 parameters and an output schema, the description is quite complete: it covers purpose, parameter semantics, and return values. Missing are usage exclusions or operational caveats (e.g., network access, timeouts), but these are not critical for straightforward enrichment. The description provides sufficient context for effective selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description thoroughly explains both parameters beyond the schema. It defines ip_address as 'IP address to enrich' and sources as 'List of sources to query (default: all available)' with explicit options. This fully compensates for the 0% schema description coverage, providing semantics the schema lacks.
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 with a specific verb and resource: 'Enrich an IP address with threat intelligence from multiple sources.' It distinguishes itself from siblings like check_ioc_reputation by emphasizing multiple sources and detailed context (reputation, geolocation, threat classifications).
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 (queries threat intel sources to provide context) but does not explicitly state when to use over alternatives or when not to use it. It lacks exclusions or comparisons to sibling tools like check_ioc_reputation, so the guidance is implied rather than explicit.
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 for behavioral disclosure. It explains that blocks can be temporary or permanent, can be consumed by various security controls, and details return fields. However, it does not mention required permissions, reversibility beyond auto_unblock, potential side effects on traffic, 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 well-structured with a concise opening statement, a short paragraph on usage, and clean Args/Returns sections. No unnecessary words or redundancy; every sentence adds value.
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?
The description covers the tool's purpose, parameters, and return values, but lacks details on error handling, prerequisites (e.g., admin rights), and the operational scope (e.g., what exactly happens when an IP is blocked). It is sufficient for straightforward use but could be more complete for a security-critical tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no parameter descriptions (0% coverage), but the description fully compensates by explaining each argument clearly, including the special value 0 for permanent, purpose of reason, and behavior of auto_unblock. This adds meaningful semantics beyond 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 tool blocks an IP address by adding it to Splunk's firewall blocklist, with a specific verb and resource. It distinguishes from sibling tools like isolate_host or add_to_threat_list by referencing Splunk's firewall blocklist and the ability to set temporary or permanent blocks.
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 blocking IP addresses in security contexts, but does not explicitly mention when to use it over alternatives, nor does it provide exclusions or edge cases. For example, it does not contrast with add_to_threat_list or isolate_host, so guidance is limited.
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 must carry the full burden. It discloses that it correlates events and returns a dictionary with summary, timeline, attack_chain, and recommendations—useful behavioral output. However, it does not explicitly state whether the operation is read-only, if it has side effects, or any access requirements. This leaves a gap in 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 well-structured and front-loaded. It opens with a clear one-sentence summary, follows with a brief explanatory sentence, then uses labeled sections for Args and Returns. Every sentence adds value without unnecessary words—efficient and organized.
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 complexity (3 params, no schema descriptions, no annotations), the description is quite thorough: it explains parameters, return structure, and the overall purpose. The main gap is the lack of explicit usage guidelines or alternative comparisons, which would make it fully complete for selection decisions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 fully does: each parameter is explained with examples and defaults. For 'indicators', it provides a concrete JSON example; for 'timeframe', it explains the time window; for 'correlation_window', it specifies seconds and the default of 2 hours. This adds substantial meaning beyond the bare 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 opens with 'Build comprehensive attack timeline from multiple indicators'—a specific verb and resource. It further explains it reconstructs a multi-stage attack by correlating events across IPs, users, and domains, clearly distinguishing this from sibling tools like find_lateral_movement or correlate_with_deeptempo_finding.
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 reconstructing attack narratives from indicators, giving context of when to use it. However, it lacks explicit exclusions or comparisons to alternatives such as find_lateral_movement or search_splunk. The guidance is clear but not fully explicit about 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.
Behavior3/5
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 behavior. It clearly describes what information is returned (unique values, top values, timestamps, related fields) and the verb 'Get' strongly implies read-only, but it never explicitly states that the tool does not modify data or whether there are any permissions, rate limits, or approximate-value caveats.
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 front-loaded with a clear one-sentence purpose, followed by a compact parameter list and a structured return contract. Every section adds value and there is no filler or repetition of information already in the schema.
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 only 3 parameters and no complex side effects, the description is largely complete: it covers purpose, all parameters, and return values. It lacks explicit usage guidelines and any edge-case limitations, but for a read-only analysis tool the provided detail is sufficient for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only provides titles and defaults, but the description adds meaningful semantics for all three parameters: field_name, indexes (explicitly noting None = all indexes), and timeframe (with format examples like '-7d'). This fully compensates for the 0% schema description 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?
The description opens with 'Get detailed information about a specific field', which clearly names the verb and resource. It further distinguishes from siblings by listing specific analysis capabilities (value distribution, statistics, temporal information, related fields) that a raw search or listing tool would not provide.
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 a use case—deep analysis of a single field—but does not explicitly state when to choose this over sibling tools like search_splunk or run_splunk_query. No alternatives or exclusions are mentioned, so the agent must infer usage context from the tool's name and capabilities.
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 of behavioral disclosure. It discloses the return format (dictionary with techniques, tactics, mitigations, detections) but does not mention potential side effects, rate limits, or whether parameters combine with AND/OR semantics. It also doesn't address the behavior when no parameters are provided, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief overview followed by Args and Returns sections. It is front-loaded with the purpose, and every sentence adds value (examples, return keys). No fluff or repetition of schema 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?
While the output schema exists and the description details the return keys, it misses critical context about parameter interactions and optionality. All parameters are optional, yet the description doesn't state whether at least one must be provided or how multiple filters combine (e.g., AND vs OR). This gap affects usability for an agent deciding how to invoke the tool.
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?
Schema description coverage is 0%, so the description must compensate, and it does well. It gives clear, useful descriptions for each parameter, including concrete examples for technique_id and tactic, and explains search_term as free-text search. It doesn't, however, clarify rules for combining multiple parameters or whether at least one is required.
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 with a specific verb and resource: 'Get context and information about MITRE ATT&CK techniques and tactics.' It distinguishes itself from sibling tools by focusing specifically on MITRE ATT&CK knowledge, unlike security tools like check_ioc_reputation or enrich_ip_with_threat_intel.
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 provides clear context for when to use the tool ('to help analysts understand and categorize security findings'), making it appropriate for threat analysis and classification. However, it does not explicitly mention when not to use it or provide alternatives among sibling tools, so it stops short of a 5.
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 must carry the full burden. It clearly states the return format (names, descriptions, search queries), but does not explicitly mention that it is a read-only operation or discuss any limitations (e.g., pagination, permissions). The verb 'list' implies safety, but explicit disclosure would be stronger.
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 for the action and one sentence for the return value. It is front-loaded with the essential information and contains no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool, the description is complete: it states the scope (all saved searches) and what is returned. The existence of an output schema further supports clarity, and the description adds value by explicitly naming the returned fields.
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 input schema has zero parameters, so there is nothing to explain. The baseline for 0 params is 4, and the description correctly omits parameter details.
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 ('List') and resource ('saved searches') with explicit scope ('all'), clearly distinguishing it from sibling tools like list_users and list_indexes. The return details further reinforce its 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?
Usage is implied by the tool's name and description but no explicit guidance is given on when to use this vs alternatives like search_splunk or run_splunk_query. There are 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.
Behavior3/5
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 clearly describes the read-only nature (pivot, returns) and details the expected output categories (summary, destination analysis, auth events, data transfer). However, it lacks any mention of potential performance costs, permission requirements, or limitations of the cross-index search, which would be valuable for an agent to know.
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 well-structured with a purpose statement, context, and a clearly formatted Args/Returns section. The second sentence about being 'critical' for SOC workflows adds context but could be seen as slight redundancy. Overall, every section earns its place, though the Returns section is somewhat verbose.
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?
The tool appears to be a complex read operation with three parameters and a rich return structure. The description explains the comprehensive output and provides examples for parameters. However, it omits details about potential resource intensity, auth requirements, or failure modes, which would make it fully complete for an agent to use safely and effectively.
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?
Although the input schema has 0% coverage, the description's Args section provides meaningful examples and semantics: ip_address with a concrete example, timeframe with Splunk format examples, and max_results clarified as 'per category'. This compensates for the bare schema and adds practical usage guidance beyond param names and types.
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 ('Pivot on IP address') and clearly identifies the resource ('across all indexes and sourcetypes') for comprehensive IP analysis. It distinguishes itself from sibling tools like search_splunk by focusing on cross-source pivoting, and the detailed return categories make its scope unmistakable.
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 states this is a critical tool for traditional SOC analyst workflows and emphasizes a complete view of IP activity, providing clear usage context. It does not explicitly mention when not to use it or alternatives, but the scope and output descriptions make it obvious this is for broad IP investigation, not targeted searches.
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 must disclose behavioral traits itself. It describes the returned dictionary structure and flags for suspicious patterns, but does not explicitly state that the tool is read-only or has no side effects, which would be important in an unannotated 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 well-structured, leading with a clear purpose statement, followed by an explanatory sentence, then neatly formatted parameter and return sections. Every line provides necessary information with no redundancy.
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?
The description covers the tool's function, parameters, and return structure, and an output schema exists, so return values are further specified. It is slightly incomplete regarding prerequisites or relationships to other tools, but overall it provides substantial context for a 4-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no parameter descriptions (0% coverage), but the description's 'Args' section explains each parameter's purpose and defaults, including dest_ip's optional behavior and threshold_mb's meaning. This fully compensates for the schema's lack of information.
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 opens with 'Calculate data transfer volumes and detect potential exfiltration,' using a specific verb and resource. It further specifies 'Analyzes outbound data transfers to identify large or suspicious uploads,' which clearly distinguishes this tool from sibling tools like 'find_lateral_movement' or 'check_ioc_reputation'.
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 clearly states the tool's context: analyzing outbound transfers for a common final attack stage. However, it does not explicitly mention when not to use it or name alternative tools for similar scenarios, so it lacks exclusions.
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 transparency burden. It discloses the primary side effect of ticket creation, mentions ITSM integration, and notes the return value. However, it does not address permissions, reversibility, duplicate behavior, or external system impact beyond the integration 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 well-structured with a concise introductory sentence, an Args block, and a Returns block. Every sentence adds value, and the overall length is appropriate for a 5-parameter tool.
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?
The description covers parameter semantics and return values, and it provides integration context. It is sufficient for invoking the tool correctly, though it lacks usage guidance and some side-effect details that would make it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no property descriptions (0% coverage), but the Args section fully compensates by explaining each parameter, listing allowed severity values, marking assignee as optional, and describing tags as a list for categorization.
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 opens with 'Create an incident ticket in the ticketing system,' using a specific verb and resource. This clearly distinguishes it from sibling tools that query, analyze, or manage security data.
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 states the tool is for tracking security incidents and integrates with ITSM platforms, providing clear context for when it is appropriate. It does not explicitly mention excluded cases or alternative tools, so it stops short of a 5.
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 burden. It reveals it is a get operation returning a dictionary and implies read-only behavior, but does not disclose error handling, permissions, or any side effects. Minimal but not misleading.
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 compact, front-loaded with the main purpose, and includes well-defined Args and Returns sections. Every sentence adds value without wasted 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's simplicity and the presence of an output schema, the description adequately covers purpose and parameter meaning. It lacks details on failure behavior, but for a metadata lookup this is not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has no description for the parameter, but the description explains 'index_name: Name of the index to get metadata for'. This fully compensates for the 0% schema coverage by adding semantic 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 'Get metadata for a specific Splunk index' with a specific verb and resource. It distinguishes itself from sibling tools like list_indexes by targeting a single index.
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 usage context is clear: use when you need metadata for a specific index. However, it does not explicitly mention alternatives or when not to use it, so it lacks explicit exclusions.
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 explains the tool's behavior (harvesting field metadata), the focus_cim option, and returns a detailed dictionary structure. It is clearly a read-only discovery operation, though it doesn't mention potential performance impacts or permission 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 well-organized with a brief intro, an Args list, and a Returns section. Every sentence provides necessary information without fluff, making it easy to scan and 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 four optional parameters and no annotations, the description covers purpose, parameter semantics, and return payload adequately. It could include error scenarios or permission caveats, but it provides sufficient information for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no parameter descriptions (0% coverage), so the description's Args section fully compensates by explaining each parameter: indexes, focus_cim, max_sample_events, and timeframe, including defaults and examples. This adds significant 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 it discovers and harvests field labels, schemas, field names, types, sample values, and metadata from Splunk indexes. This is a specific verb+resource that distinguishes it from sibling tools like search_splunk or list_indexes.
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 provides context for when to use it ('to support DeepTempo training and evaluation') and mentions the CIM field option, but it does not explicitly contrast with alternatives like get_field_summary or state when not to use it. Usage is implied rather than exhaustively specified.
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 disclosing behavioral traits. It states the action (get/list) but does not explicitly mention that the tool is read-only, safe, or has no side effects. It also omits any information about authentication, rate limits, or other behavioral aspects. The verbs imply a read operation, but this is not explicitly disclosed.
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 front-loads the core purpose and immediately follows with a sibling reference. Every word earns its place, with no unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (no parameters, no nested objects), and an output schema is present, so the description need not explain return values. The provided information fully covers what the tool does and how it relates to health_check, making it complete for this low-complexity tool.
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 the baseline is 4. The description does not need to explain parameter details since there are none, and the schema is empty. This 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's verb and resources: 'Get basic Splunk connection information and list available apps'. It also explicitly distinguishes itself from the sibling tool health_check by explaining 'same as health_check but for endpoint consistency', which clarifies its role as an endpoint-consistent variant.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance by referencing the alternative tool health_check and noting they are the same, but this one is for endpoint consistency. This tells the agent when to use this tool instead of health_check, though it doesn't compare against other siblings.
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 the tool executes arbitrary SPL, defines parameters and defaults, and returns a list of results. However, it does not explicitly warn about potential side effects of arbitrary SPL or mention error behavior, leaving some ambiguity.
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 compact docstring with the purpose in the first line, followed by an Args list and Returns line. Every sentence adds necessary information with no filler.
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?
The description covers the alias relationship, all parameters, and return type, making it sufficient for basic selection and invocation. However, it lacks guidance on error handling, authentication, or performance implications of arbitrary queries, which would be useful for a tool this powerful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining every parameter: query, earliest_time, latest_time, and max_results, each with a clear meaning and default values drawn from 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 states a clear verb and resource: 'Execute arbitrary SPL query.' It also distinguishes itself from siblings by explicitly identifying as an alias for search_splunk, which differentiates it from the near-duplicate 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use this tool: it is an alias for search_splunk, intended for compatibility with the label harvester. This implies using search_splunk for new integrations, though it does not explicitly exclude other cases.
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 provided, the description carries the full burden and does a good job by specifying supported IOC types and detailing the return structure (verdict, confidence, threat_categories, recommendations). This provides predictability about behavior, though it does not disclose potential side effects, data sources, or limitations like rate limits. Still, for a read-only lookup tool, this is solid.
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 well-structured with clear sections for purpose, Args, and Returns. It is concise, front-loaded with the main purpose, and every sentence adds useful information. No wasted words or repetitive content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 params, 1 required) and the description covers purpose, parameter semantics, and return values in a structured format. The included output schema (Returns) makes the behavior fully understandable. No critical gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description's Args section fully explains both parameters: ioc_value (the IOC to check with examples) and ioc_type (allowed enum values and the 'auto' detect behavior). This goes far beyond the bare schema, which only provides names and types.
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: 'Check the reputation of an Indicator of Compromise (IOC).' It names the specific verb 'check' and the resource 'reputation of an IOC,' and further distinguishes itself by listing supported IOC types (IPs, domains, file hashes, URLs). This differentiates it from sibling tools like enrich_ip_with_threat_intel, which is IP-specific.
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 quick reputation checks of various IOC types, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. It lacks explicit 'use this when...' or 'instead of...' guidance, so it only meets the implied usage level.
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 explains the process and return values, but does not disclose whether the operation is read-only, requires special permissions, or has side effects. This is a gap for a tool that interacts with two systems.
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?
Well-structured and front-loaded: first sentence states the core purpose, second provides strategic context, then clean Args/Returns sections. Every sentence adds value, and the details on subfields and outputs justify the length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is comprehensive for the tool's complexity: it covers purpose, usage context, all three parameters (including nested object structure), and return fields. With an output schema present, it does not need to further detail return formats, making this highly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates by explaining finding_id, deeptempo_data with its nested structure (src_ip, dest_ip, timestamp, confidence, mitre_techniques), and timeframe_padding with its default. This is exactly what an agent needs to invoke the tool 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 uses a specific verb ('Correlate') with a clear resource ('DeepTempo finding') and target ('Splunk evidence'). It clearly distinguishes itself from siblings like search_splunk by positioning as the cross-platform bridge for AI-native investigation.
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?
Provides clear context: it is 'the key tool for AI-native investigation' and bridges DeepTempo anomalies with Splunk logs. It gives situational guidance but does not explicitly state when not to use it or name alternative tools.
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 provided, the description carries the full burden of behavioral disclosure. It explains the detection methods (statistical, ML, baseline), the parameters affecting behavior (sensitivity, timeframe), and the return structure (anomalies, baseline, confidence, recommendations). This provides substantial transparency beyond the tool name, though it does not explicitly state whether the tool is read-only or has 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a short opening sentence, a bulleted Args list, and a bulleted Returns list. Every sentence earns its place, providing necessary context without unnecessary filler. It is appropriately sized for a tool with five parameters and a complex return value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has five parameters, no schema descriptions, and no annotations, the description is remarkably complete. It covers all parameters, describes the detection methods, and details the output dictionary. This is sufficient for an agent to understand what the tool does, when to use it, and what it returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates with an 'Args' section that provides a one-line meaning for each parameter: index, field, timeframe, sensitivity, and method (including allowed values for method and sensitivity). This adds substantial meaning beyond the input schema's bare property names and defaults.
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: 'Detect statistical anomalies in time-series data' with specific detail about identifying 'unusual patterns, spikes, or outliers in security data that may indicate threats.' This distinguishes it from sibling tools like 'identify_rare_events' and 'baseline_normal_behavior' by focusing on anomaly detection in time-series security data.
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 threat detection in security data ('may indicate threats') but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. The sibling tools include closely related ones like 'identify_rare_events' and 'baseline_normal_behavior,' so clearer differentiation would improve guidance.
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 provided, the description carries the full burden. It discloses that the operation is a read ('Get information') and enumerates the returned fields, conveying a non-destructive profile. It does not explicitly state 'does not modify data' or 'requires authentication', but 'currently authenticated user' implies an auth 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 concise and well-structured: a clear opening sentence followed by bullet points listing the retrieved information and a return type. Every sentence earns its place, and it's not padded with fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter tool with an output schema, the description is complete. It explains the purpose, what data is retrieved, and the return type. No further context is needed for an agent to select and invoke it correctly.
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 takes zero parameters, and the schema confirms this (100% coverage with empty properties). Per the rubric, the baseline for zero parameters is 4, and the description adds context about the return value, which is helpful.
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 ('Get information') and clearly identifies the resource ('currently authenticated user'). It lists the specific data categories returned, which distinguishes it from sibling tools like list_users that deal with all users.
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 clearly implies usage context: use this tool when you need information about the currently authenticated user. It doesn't explicitly mention alternatives or exclusions, but the purpose is clear enough to guide tool selection alongside siblings like list_users.
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 takes on the burden and largely succeeds: it discloses that the tool transforms data, optionally saves to a file, and returns a dictionary with export_data, file_path, and summary. It stops short of fully detailing side effects like file overwrite behavior or error conditions, but provides more than 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a one-sentence summary followed by Args and Returns sections. It is appropriately detailed without being verbose; every sentence adds information, and the layout allows quick scanning.
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?
The description covers purpose, input provenance, parameters, and return value structure. It even notes the format is 'generic and adaptable.' It does not discuss error handling, permissions, or file overwrite semantics, but given the output schema and detailed parameter documentation, it is sufficiently complete for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates excellently. Each parameter (field_data, output_format, save_to_file, file_path) receives a meaningful explanation beyond the schema's bare type/default information, including the expected value for output_format and the default file path.
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 opens with a specific verb+resource: 'Export harvested field labels in DeepTempo-compatible format.' It further clarifies the transformation from harvest_labels() output into a consumable format for DeepTempo training/evaluation, distinguishing it from siblings like harvest_labels and correlate_with_deeptempo_finding.
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 clearly states the input comes from harvest_labels() and the intended purpose ('for training and evaluation'), giving strong contextual guidance on when to use it. It does not explicitly mention when not to use it or name alternatives, so it stops short of a 5.
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 burden of behavioral disclosure. It explains the mechanism ('restricting network access'), implementation options (NAC, endpoint security, SDN/firewall), and isolation levels ('full', 'partial', 'monitoring'). It also discloses that duration 0 means manual removal, providing useful operational behavior. However, it does not mention permissions, reversibility, or impact on existing connections, which would make it 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It starts with the purpose, then briefly explains the mechanism, followed by a clear Args list and a Returns statement. There is minimal redundancy, and every sentence contributes useful information.
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?
The description covers purpose, parameters, and return type adequately for a 4-parameter tool. It lacks explicit usage exclusions or safety warnings, but the isolation levels and duration behavior provide sufficient operational context. The presence of an output schema reduces the need to detail return values beyond what is given.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates fully by explaining every parameter. It defines hostname as 'Hostname or IP', isolation_level with its enum-like values, reason, and duration_hours including the special '0 = manual removal' meaning. This adds substantial semantic value beyond the bare schema 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?
The description opens with a clear, specific action: 'Isolate a compromised host from the network.' It then reinforces the purpose with 'Quarantines a host by restricting its network access.' This clearly distinguishes it from siblings like block_ip_address, which blocks a specific IP rather than isolating a host.
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 implies usage context by mentioning 'compromised host,' telling the agent when to use it. However, it does not explicitly mention alternatives or when not to use it, such as differentiating from block_ip_address or other network-level tools. Despite that, the context is clear enough for appropriate selection.
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 burden. It explicitly states the operation (list) and the return content (metadata with app, fields, accelerated fields). It does not mention permissions or side effects, but as a read-only list operation, this is sufficient.
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 two concise sections: the action and the return format. Every sentence earns its place without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with an output schema, the description fully covers what the tool does and what it returns. No additional context is necessary.
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 4 applies. The description adds no parameter information, but none is needed.
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 all KV store collections across apps, with a specific verb+resource+scope. This distinguishes it from siblings like list_indexes and list_saved_searches.
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 context is clear: this is for listing KV store collections. While no explicit alternatives or exclusions are given, the purpose is specific enough that an agent would know when to use it versus other list tools.
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 are provided, so the description carries the full burden. It discloses the main side effect (pushing notifications to multiple channels) and the return type (delivery status dictionary). It also implies a prerequisite ('configured channels'). However, it does not cover partial failure behavior or rate limits, which would be richer 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 front-loaded with the primary purpose, followed by a concise supporting sentence and a structured Args/Returns block. Every sentence adds value; there is no redundancy or unnecessary elaboration, making it easy to scan and parse quickly.
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 tool with 4 parameters, no annotations, and no schema descriptions, this description provides a solid overview of the action, parameters, and return value. It is sufficiently complete for an agent to select the tool and invoke it correctly, though valid severity values and error handling details are not specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the Args section thoroughly explains all four parameters: message, channels (with acceptable values enumerated), severity (alert level), and include_details. This is especially valuable for the channels parameter, which has no enum in the schema, and fully compensates for the schema's lack of 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 first sentence clearly states the tool sends alert notifications to configured channels. The second sentence lists the supported services (Slack, Teams, PagerDuty, email, SMS), making the purpose specific and unambiguous, even without any sibling competing for the same function.
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 implies use for notifying response teams in alert scenarios ('to ensure rapid response team awareness'). While it does not explicitly state when not to use or name alternatives, no sibling tool serves the same function, so the context is clear enough for an agent to decide when to invoke 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?
With no annotations provided, the description carries the full burden. It clearly discloses that the tool analyzes various behavioral signals and returns a dictionary with risk score, indicators, timeline, affected hosts, and recommendations. This implies a read-only analysis operation, and the output structure is transparent. It does not mention side effects or permissions, but the analysis nature makes these less critical.
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 well-structured with a one-sentence summary followed by clear Args and Returns sections. Every sentence earns its place, and the content is front-loaded with the primary purpose. It is concise while covering all necessary aspects.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a three-parameter tool with an output schema, the description covers purpose, usage context, each parameter's semantics, and the exact structure of the return value. This is comprehensive for an analyst to understand what the tool does and what it returns, requiring no additional inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 does so effectively: source_ip is 'IP address of potentially compromised host', time_window is 'Time window to analyze' with default '-7d', and threshold is 'Minimum number of unique destinations to flag' with default 5. These explanations go beyond the raw schema types and clarify each parameter's purpose.
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 opens with a specific verb and resource: 'Detect lateral movement patterns from a potentially compromised host.' This clearly differentiates from sibling tools like pivot_by_ip or calculate_data_exfiltration by focusing on lateral movement identification.
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 provides clear context for use: analyzing authentication attempts, rapid connections, privilege escalation indicators, and unusual protocols to spot lateral movement typical of advanced threats. It does not explicitly list exclusions or alternative tools, but the context is sufficient to infer when 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.

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