ms-sentinel-mcp-server

Overview Schema Related Servers Score Discussions

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific Sentinel resources (e.g., incidents, rules, connectors) with clear action verbs, though some overlap exists between sentinel_logs_search and sentinel_logs_search_with_dummy_data, and between markdown_template_get and tool_docs_get. The descriptions help clarify differences, but agents might occasionally confuse similar tools.
Naming Consistency5/5
Tool names follow a highly consistent snake_case pattern with a clear verb_noun structure throughout (e.g., sentinel_incident_get, sentinel_analytics_rule_list). All tools adhere to this convention, making them predictable and easy to parse, with no mixing of styles or chaotic naming.
Tool Count2/5
With 49 tools, the count is excessive for a single server, likely overwhelming for agents and indicating poor scoping. While Sentinel is a broad domain, this many tools suggests fragmentation or redundancy, such as multiple counting tools (e.g., sentinel_analytics_rules_count_by_tactic, sentinel_analytics_rules_count_by_technique) that could be consolidated.
Completeness5/5
The tool set provides comprehensive coverage of the Sentinel domain, including CRUD operations for incidents, rules, connectors, watchlists, and metadata, plus utilities for logs, queries, and documentation. No obvious gaps exist; agents can perform full lifecycle management and analysis tasks without dead ends.
Average 2.6/5 across 49 of 49 tools scored. Lowest: 1.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior1/5
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 but offers no details. It doesn't indicate if this is a read-only operation, requires authentication, has rate limits, returns structured data, or involves side effects. The vague 'Get' provides no transparency into how the tool behaves or what to expect from its execution.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence with no wasted words, making it highly concise. However, it's under-specified rather than optimally structured—it lacks front-loaded critical details but isn't verbose. This efficiency in length, despite content gaps, justifies a score above average for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (retrieving a specific resource), lack of annotations, 0% schema coverage, no output schema, and many sibling tools, the description is severely incomplete. It doesn't clarify what 'specific' means, how to identify the watchlist, what data is returned, or how it differs from related tools. This inadequacy fails to provide the context needed for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, meaning the schema provides no semantic information. The description adds no parameter details—it doesn't explain what 'kwargs' should contain (e.g., a watchlist ID, name, or filter criteria) or how to format it. This fails to compensate for the schema's lack of coverage, leaving parameters entirely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a specific Sentinel watchlist' restates the tool name with minimal elaboration. It uses a verb ('Get') and resource ('Sentinel watchlist'), but lacks specificity about what 'get' entails (e.g., retrieve metadata, fetch details) and doesn't distinguish it from siblings like 'sentinel_watchlists_list' or 'sentinel_watchlist_item_get'. This is a tautological expansion of the name, earning a low score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention siblings like 'sentinel_watchlists_list' for listing all watchlists or 'sentinel_watchlist_item_get' for items within a watchlist, nor does it specify prerequisites or contexts for retrieval. This absence of usage instructions makes it misleading for an agent trying to select the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the action ('Get workspace information') without any details on permissions required, rate limits, response format, error conditions, or whether it's a read-only operation. The parenthetical note about refactoring and MCP compliance is irrelevant to behavior. This leaves the agent with critical gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but inefficiently structured. The core purpose is stated upfront ('Get workspace information'), which is good, but the parenthetical '(refactored, MCP-compliant)' wastes space on non-functional details. It could be more concise by omitting the parenthetical and adding minimal useful context instead.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a tool with 1 undocumented parameter, no annotations, and no output schema), the description is severely incomplete. It doesn't explain what workspace information is retrieved, how to use the 'kwargs' parameter, what the output looks like, or any behavioral constraints. For a tool in a security context (Sentinel) with many siblings, this leaves the agent unable to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, meaning the schema provides no semantic information. The description adds nothing about what 'kwargs' should contain (e.g., workspace ID, filter criteria) or how to format it. For a tool with undocumented parameters, the description fails to compensate, leaving the agent guessing about required inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Get workspace information' which provides a clear verb ('Get') and resource ('workspace information'), establishing its basic purpose. However, it doesn't specify what type of workspace (e.g., Microsoft Sentinel workspace) or what information is retrieved, and the parenthetical '(refactored, MCP-compliant)' adds no functional clarity. It doesn't distinguish from siblings like 'sentinel_metadata_get' or 'sentinel_authorization_summary' which might also retrieve workspace-related data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, context (e.g., for Sentinel security operations), or comparison to sibling tools like 'sentinel_metadata_get' that might retrieve similar information. The agent must infer usage from the tool name alone, which is insufficient for informed selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states what the tool does at a high level, with no information about permissions, rate limits, output format, error handling, or whether it's a read-only operation. This is inadequate for a tool with unknown behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple counting operation and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema description coverage, no output schema, and one undocumented parameter, the description is completely inadequate. It doesn't compensate for the missing structured information, leaving users guessing about how to use the tool and what to expect from it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'kwargs' with 0% description coverage, and the tool description provides no information about parameters. The description doesn't explain what 'kwargs' should contain, how to specify tactics, or any filtering options. This leaves the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Count Sentinel analytics rules by tactic' clearly states the action (count) and resource (Sentinel analytics rules), but it's somewhat vague about what 'by tactic' means operationally. It distinguishes from siblings like 'sentinel_analytics_rule_list' (which lists rules) and 'sentinel_analytics_rules_count_by_technique' (which counts by technique instead of tactic), but lacks specificity on the counting mechanism.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention prerequisites, context for counting by tactic, or compare it to similar tools like 'sentinel_analytics_rules_count_by_technique' or 'sentinel_analytics_rule_templates_count_by_tactic'. Users must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the action without any details on permissions required, rate limits, pagination, or what the output looks like (e.g., list format, error handling). This is inadequate for a tool with potential security or operational implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single phrase 'List data connectors', which is front-loaded and wastes no words. It efficiently communicates the core action, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by the sibling tools (e.g., security operations), no annotations, no output schema, and 0% parameter coverage, the description is severely incomplete. It fails to address critical aspects like authentication needs, data format, or error conditions, making it insufficient for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter (kwargs) with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' represents (e.g., filtering options, configuration) or how to use it, leaving the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List data connectors' clearly states the action (list) and resource (data connectors), providing basic purpose. However, it lacks specificity about what data connectors are in this context (e.g., Sentinel security connectors) and doesn't distinguish from sibling tools like sentinel_connectors_get, which suggests a similar domain but different operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this is for browsing all connectors versus filtered searches, or how it relates to sentinel_connectors_get. The description offers no context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 fails to describe key traits: whether this is a read-only or mutating operation, authentication requirements, rate limits, error handling, or what the output looks like (e.g., raw logs, structured data). The description only states the action without behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's action and target. It's appropriately sized for a basic description, though its brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a query tool with no annotations, 0% schema coverage, no output schema, and many sibling tools), the description is incomplete. It lacks essential details: parameter guidance, behavioral traits, usage context, and output expectations. This makes it inadequate for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one undocumented parameter 'kwargs' of type string. The description adds no meaning beyond the schema—it doesn't explain what 'kwargs' should contain (e.g., KQL query syntax, time range, workspace ID), format, or examples. This leaves the parameter semantics entirely unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Run a KQL query') and target ('against Azure Monitor'), which gives a basic purpose. However, it's vague about what 'Azure Monitor' specifically refers to in this context (e.g., logs, metrics, specific tables) and doesn't distinguish it from sibling tools like 'sentinel_logs_search_with_dummy_data' or 'log_analytics_saved_searches_list', which limits its clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication, workspace context), typical use cases (e.g., security investigations, monitoring), or exclusions (e.g., when to use 'sentinel_logs_search_with_dummy_data' for testing). This leaves the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Get details' without explaining what 'details' include, whether it's a read-only operation, if it requires authentication, rate limits, error handling, or the response format. This leaves critical behavioral traits unspecified for a tool with one parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized for a simple 'get' operation and front-loaded with the core action, though it lacks depth due to under-specification rather than conciseness issues.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a 'get' operation with one parameter), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain what 'details' are returned, how to use the parameter, or behavioral aspects, making it inadequate for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' should contain (e.g., the ID format, expected string structure) or add any meaning beyond the bare schema. With low schema coverage, the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Get details') and resource ('specific Sentinel metadata by ID'), which provides a basic purpose. However, it's vague about what 'details' include and doesn't distinguish from siblings like 'sentinel_metadata_list' (which likely lists metadata without details) or 'sentinel_incident_get' (which gets incident details). The purpose is clear but lacks specificity and sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid ID), exclusions, or compare to siblings like 'sentinel_metadata_list' for listing metadata or other 'get' tools for different resource types. The description only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does ('Collect metrics') without any details on traits such as whether it's read-only or destructive, authentication requirements, rate limits, or response format. This leaves critical behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly, though it lacks depth.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a metrics collection tool with no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It fails to provide necessary context such as what metrics are collected, how to interpret results, or behavioral traits, making it insufficient for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, meaning the schema provides no semantic information. The description adds no parameter details beyond the tool's purpose, failing to explain what 'kwargs' should contain or how to format it, which is inadequate given the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Collect metrics for Sentinel threat intelligence indicators', which provides a clear verb ('Collect') and resource ('metrics for Sentinel threat intelligence indicators'). However, it lacks specificity about what types of metrics are collected or how they differ from other Sentinel-related tools in the sibling list, making it somewhat vague rather than fully distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple Sentinel-related tools in the sibling list (e.g., sentinel_ti_indicator_get, sentinel_analytics_rule_list), there is no indication of context, prerequisites, or exclusions for using this metrics collection tool, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action without any details on traits like read-only vs. destructive (implied read-only but not confirmed), rate limits, authentication needs, output format, pagination, or error handling. This is inadequate for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to scan. Every element ('List users', 'Entra ID', 'Microsoft Graph API') adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (API integration tool), lack of annotations, 0% schema coverage, and no output schema, the description is severely incomplete. It omits critical context like parameter usage, behavioral traits, authentication, and output details. This leaves the agent with insufficient information to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' represents (e.g., query filters, pagination options) or how to use it. With low schema coverage, the description fails to compensate, leaving parameters undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List users') and resource ('in Entra ID (Azure AD)'), and specifies the API used ('via Microsoft Graph API'). It distinguishes from siblings like 'entra_id_get_user' (single user retrieval) and 'entra_id_list_groups' (different resource type), though it doesn't explicitly contrast them. The purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication requirements), when to choose this over 'entra_id_get_user' for single users, or any limitations (e.g., pagination, filtering capabilities). Usage context is implied by the name but not articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('Count...') without explaining how it behaves—e.g., whether it requires authentication, has rate limits, returns aggregated data, or handles errors. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, clearly front-loading the core purpose. It is appropriately sized for a simple counting operation, though its brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a counting operation with a parameter), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It fails to explain parameter usage, behavioral traits, or output format, making it insufficient for an agent to use the tool effectively without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one required parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It does not explain what 'kwargs' should contain (e.g., filter criteria, MITRE technique IDs) or its format, leaving the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Count') and resource ('Sentinel analytics rules') with a specific grouping criterion ('by MITRE technique'), making the purpose unambiguous. It distinguishes from some siblings like 'sentinel_analytics_rule_list' (which lists rules) but not explicitly from 'sentinel_analytics_rules_count_by_tactic' (which counts by tactic instead of technique).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 sibling tools like 'sentinel_analytics_rules_count_by_tactic' for counting by tactic or 'sentinel_analytics_rule_list' for listing rules, leaving the agent to infer usage context based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states only the basic action ('Get') without any information about authentication requirements, rate limits, error conditions, return format, or whether it's read-only or has side effects. For a tool with zero annotation coverage, this is a significant 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 a single, focused sentence with zero wasted words. It's front-loaded with the core purpose and avoids unnecessary elaboration. While it lacks detail, what's present is structurally efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a tool for retrieving security analytics templates), lack of annotations, 0% schema coverage, no output schema, and incomplete parameter documentation, the description is severely inadequate. It doesn't provide enough context for an agent to understand how to invoke the tool correctly or interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, meaning the schema provides no semantic information. The description adds no parameter details whatsoever—it doesn't explain what 'kwargs' should contain (e.g., a template ID or filter criteria), expected format, or examples. This leaves the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('a specific Sentinel analytics rule template'), making the purpose immediately understandable. It distinguishes from sibling tools like 'sentinel_analytics_rule_templates_list' by specifying retrieval of a single template rather than listing multiple. However, it doesn't fully differentiate from 'sentinel_analytics_rule_get' (which gets rules, not templates), so it's not perfectly specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a template ID), compare to sibling tools like 'sentinel_analytics_rule_templates_list' for browsing, or specify use cases. The agent must infer usage from the tool name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the purpose without any information on permissions required, rate limits, side effects, or output format. For a tool with no annotation coverage, this is inadequate as it fails to describe how the tool behaves beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it easy to parse. It is appropriately sized for the tool's apparent simplicity, though this conciseness comes at the cost of missing important details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a counting operation with one parameter and no output schema or annotations, the description is incomplete. It lacks details on parameter usage, behavioral traits, and expected results, making it insufficient for an AI agent to invoke the tool correctly without additional context or trial-and-error.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('kwargs') with 0% description coverage, and the tool description does not mention parameters at all. This leaves the parameter undocumented in both schema and description, failing to compensate for the low schema coverage. The agent has no guidance on what 'kwargs' should contain or how to use it.
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 ('Count') and the resource ('Sentinel analytics rule templates by tactic'), making the purpose evident. However, it does not differentiate from sibling tools like 'sentinel_analytics_rule_templates_count_by_technique' or 'sentinel_analytics_rules_count_by_tactic', which have similar naming patterns but target different scopes (e.g., techniques vs. rules vs. templates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'sentinel_analytics_rule_templates_list' for listing templates or 'sentinel_analytics_rule_templates_count_by_technique' for counting by technique. There is no mention of prerequisites, context, or exclusions, leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get' which implies a read operation, but doesn't disclose any behavioral traits such as authentication needs, rate limits, error handling, or what the response looks like. This leaves significant gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a security tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on parameters, behavior, output format, and differentiation from siblings, making it inadequate for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the description doesn't add any meaning beyond the tool name. It doesn't explain what 'kwargs' should contain (e.g., the connector ID format or other details), leaving the parameter undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('a specific data connector by ID'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'sentinel_connectors_list' or explain what a 'data connector' is in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'sentinel_connectors_list' for listing connectors or other get tools for different resources. The description implies usage when you have a specific connector ID, but offers no explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implied read-only), but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what 'detailed information' includes. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple tool and front-loaded with the core purpose, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain the parameter, return values, or behavioral traits, leaving the agent with insufficient context to use the tool effectively. While concise, it lacks necessary details for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' should contain (e.g., an incident ID or query parameters), leaving the parameter completely undocumented. This fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Get detailed information about a specific Sentinel incident', which is clear but vague. It specifies the verb 'Get' and resource 'Sentinel incident', but doesn't distinguish it from sibling tools like 'sentinel_incident_list' or explain what 'detailed information' entails. This is a basic but adequate statement of purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'sentinel_incident_list' for listing incidents or specify prerequisites such as needing an incident ID. Without any usage context or exclusions, the agent must 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.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. It doesn't indicate whether this is a read-only operation, what permissions are required, if there are rate limits, pagination behavior, or what format the results take. 'List' implies a read operation but lacks critical operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a basic listing operation and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of security incident listing (likely involving filtering, pagination, permissions), no annotations, no output schema, and 0% parameter documentation, this description is completely inadequate. It provides only the most basic purpose statement without any operational or contextual details needed for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for its single 'kwargs' parameter, and the tool description provides absolutely no information about what this parameter expects or how to use it. The description doesn't mention parameters at all, leaving the agent with no semantic understanding of required inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('security incidents in Microsoft Sentinel'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'sentinel_incident_get' which retrieves a single incident, leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'sentinel_incident_get' for single incidents or 'sentinel_logs_search' for broader data queries. There's no mention of prerequisites, filtering capabilities, or comparison to similar list operations in the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states this is a 'Get' operation but doesn't disclose whether it's read-only, requires specific permissions, has rate limits, returns structured data or errors, or what happens if the ID doesn't exist. This is inadequate for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple lookup tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a security tool (Sentinel), zero annotations, no output schema, and undocumented parameters, the description is severely incomplete. It doesn't explain what 'details' are returned, error conditions, authentication requirements, or how this fits into the broader Sentinel context with its many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage with one parameter named 'kwargs' of type string. The description mentions 'by ID' but doesn't specify that this ID should be passed in 'kwargs', what format it should have, or provide any examples. With low schema coverage, the description fails to compensate for the undocumented parameter.
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 ('Get details') and resource ('a specific Sentinel source control by ID'), making the purpose understandable. However, it doesn't distinguish this tool from similar siblings like 'sentinel_connectors_get' or 'sentinel_watchlist_get' which follow the same 'get by ID' pattern for different Sentinel resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling 'sentinel_source_controls_list' for listing all source controls, nor does it specify prerequisites like needing a specific ID format or authentication context. Usage is implied but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get' which implies a read operation, but doesn't disclose any behavioral traits: no information on authentication requirements, rate limits, error conditions, response format, or whether it's idempotent. For a tool with no annotation coverage, this is a significant 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 a single, clear sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a read operation with one undocumented parameter), no annotations, and no output schema, the description is incomplete. It lacks details on parameter usage, behavioral context, and expected outputs, which are essential for an AI agent to invoke this tool correctly. The conciseness doesn't compensate for these gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage with one required parameter named 'kwargs' of type string, which is completely undocumented. The description adds no meaning beyond the schema—it doesn't explain what 'kwargs' should contain (e.g., watchlist ID, item ID, query parameters) or provide any examples. With low schema coverage, the description fails to compensate.
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 ('Get') and target resource ('a specific item from a Sentinel watchlist'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'sentinel_watchlist_get' or 'sentinel_watchlist_items_list', but the specificity of 'item' versus 'watchlist' or 'items' provides some implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'sentinel_watchlist_items_list' for listing multiple items or 'sentinel_watchlist_get' for watchlist metadata. It lacks context about prerequisites, like needing a watchlist ID or item identifier, which is critical given the single undocumented parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't cover critical aspects like pagination, rate limits, authentication needs, or what 'all' entails (e.g., scope, limits). This leaves significant gaps for an agent to understand how to invoke it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it easy to parse. It's front-loaded with the core action and resource, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a list operation with 1 undocumented parameter, no annotations, and no output schema), the description is insufficient. It doesn't explain the parameter, behavioral traits, or return format, leaving the agent with minimal guidance beyond the basic purpose. This is particularly problematic for a tool with no structured support from annotations or schema descriptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 required parameter ('kwargs') with 0% description coverage, meaning the schema provides no details about its purpose. The description adds no parameter information beyond the tool name, failing to explain what 'kwargs' represents (e.g., filtering options, pagination tokens) or how to use it, which is inadequate given the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all Sentinel watchlists' clearly states the verb ('List') and resource ('Sentinel watchlists'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'sentinel_watchlist_get' (which retrieves a specific watchlist) or 'sentinel_watchlist_items_list' (which lists items within a watchlist), leaving room for ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as whether it's for retrieving all watchlists in bulk versus specific ones, or how it relates to siblings like 'sentinel_watchlist_get' for individual watchlists.
Agents often have multiple tools that could apply. Explicit usage guidance like "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 states the tool retrieves a user but doesn't mention authentication requirements, rate limits, error handling (e.g., if the user isn't found), or what the output looks like (e.g., user details). For a read operation with zero annotation coverage, this is a significant 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 a single, efficient sentence that front-loads the core purpose ('Get a user from Entra ID') and adds necessary detail ('by object ID, UPN, or email address'). There is no wasted verbiage, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a user lookup in Entra ID), lack of annotations, no output schema, and poor parameter documentation (0% schema coverage with minimal description help), the description is incomplete. It doesn't cover authentication, output format, error cases, or parameter usage, leaving critical gaps for an AI agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, meaning the schema provides no details about what this parameter should contain. The description mentions lookup methods ('by object ID, UPN, or email address') but doesn't explain how to specify these in 'kwargs' (e.g., format, syntax, or examples). This fails to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('a user from Entra ID (Azure AD)'), specifying the action and target. It distinguishes from siblings like 'entra_id_list_users' by focusing on retrieving a single user rather than listing multiple. However, it doesn't explicitly differentiate from 'entra_id_get_group' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'entra_id_list_users' for multiple users or other lookup methods. It mentions lookup methods ('by object ID, UPN, or email address') but doesn't specify when to choose one over another or any prerequisites. This leaves the agent without clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action and API. It doesn't disclose behavioral traits such as pagination, rate limits, authentication requirements, error handling, or whether it's read-only (implied by 'List' but not explicit). This leaves significant gaps for agent understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's purpose and API. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (list operation with 1 undocumented parameter), no annotations, and no output schema, the description is incomplete. It lacks details on parameters, behavioral context, and return values, making it insufficient for reliable agent use despite its conciseness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the single parameter 'kwargs' is undocumented in both schema and description. The description adds no meaning beyond the schema, failing to explain what 'kwargs' should contain (e.g., query parameters, filters) or its format, leaving the parameter semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('groups in Entra ID'), and specifies the API used ('via Microsoft Graph API'). It distinguishes from siblings like 'entra_id_get_group' (singular retrieval) and 'entra_id_list_users' (different resource type). However, it doesn't explicitly differentiate scope from all siblings, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'entra_id_list_users' or other list tools in the sibling set. It lacks context about prerequisites, filtering capabilities, or performance considerations, offering minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only list operation but doesn't specify details like authentication requirements, rate limits, pagination, or return format. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a list operation with 1 parameter, no annotations, and no output schema, the description is incomplete. It lacks parameter details, behavioral context, and usage guidelines, making it insufficient for an agent to fully understand how to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter information beyond what the input schema provides. With 0% schema description coverage and 1 required parameter ('kwargs'), the description fails to explain what 'kwargs' represents or how to use it, leaving the parameter undocumented and unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all saved searches in a Log Analytics workspace'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling 'log_analytics_saved_search_get', which appears to retrieve a single saved search, so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, context, or comparisons to sibling tools like 'log_analytics_saved_search_get' or other list tools in the server, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a read operation ('Get'), but doesn't mention authentication requirements, error handling, rate limits, or what happens if the saved search doesn't exist. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers the basic purpose but fails to address parameter usage, behavioral context, or output expectations, which are critical for a tool with undocumented inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' should contain (e.g., saved search name, ID, or workspace details), leaving the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('a specific saved search from a Log Analytics workspace'), making the purpose immediately understandable. It doesn't explicitly differentiate from its sibling 'log_analytics_saved_searches_list', but the distinction is implied through 'specific' versus 'list' naming.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'log_analytics_saved_searches_list' or other get/list siblings. It lacks context about prerequisites, such as needing a saved search name or ID, or when this is appropriate over listing all searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "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 states the tool lists templates and descriptions, implying a read-only operation, but fails to mention critical details like whether it returns all templates at once, supports pagination, or has rate limits. This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for a simple list operation, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a list tool with one undocumented parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., format, structure), parameter usage, or behavioral constraints, making it inadequate for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one required parameter 'kwargs' with 0% description coverage, and the tool description provides no information about parameters. This leaves the parameter undocumented in both schema and description, failing to compensate for the low schema coverage and not adding any semantic 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 verb ('List') and resource ('available markdown templates and their descriptions'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling 'markdown_template_get' (which presumably retrieves a single template), leaving room for ambiguity in sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'markdown_template_get' or other list tools in the server. It lacks context about prerequisites, such as whether authentication or specific permissions are required, or any exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get details' which implies a read-only operation, but fails to describe any behavioral traits like authentication requirements, rate limits, error handling, or what 'details' include (e.g., rule configuration, status). This leaves significant gaps for a tool with no structured safety hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly, which is ideal for conciseness in tool descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a 'get details' operation with no annotations, 1 parameter at 0% coverage, and no output schema, the description is incomplete. It doesn't cover parameter semantics, behavioral context, or return values, making it inadequate for an agent to use the tool effectively without additional guesswork or documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description adds no information about parameters. It doesn't explain what 'kwargs' should contain (e.g., a rule ID or name), its format, or examples, failing to compensate for the lack of schema documentation and leaving the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get details') and resource ('a specific analytics rule'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'sentinel_analytics_rule_list' or other get tools in the server, missing explicit differentiation that would warrant a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'sentinel_analytics_rule_list' for listing rules or other get tools in the server. It lacks context about prerequisites, such as needing a rule identifier, or exclusions, leaving the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'key fields' but doesn't specify what those are, whether the list is paginated, if there are rate limits, or what permissions are required. This leaves significant gaps in understanding how the tool behaves beyond a simple list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that directly states the tool's purpose. It is front-loaded with no wasted words, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, 0% schema description coverage, no output schema, and multiple sibling tools, the description is insufficient. It doesn't explain parameters, return values, behavioral constraints, or differentiation from alternatives, leaving the agent with inadequate context for proper tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. This leaves the parameter completely undocumented, failing to compensate for the lack of schema details and making it unclear how to use the tool effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all analytics rules') and specifies the scope ('with key fields'), which distinguishes it from generic list operations. However, it doesn't explicitly differentiate from sibling tools like 'sentinel_analytics_rule_templates_list' or 'sentinel_analytics_rule_get', leaving some ambiguity about when to use this specific tool versus 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 provides no guidance on when to use this tool versus alternatives, such as 'sentinel_analytics_rule_get' for single rules or 'sentinel_analytics_rule_templates_list' for templates. It lacks context about prerequisites, filtering options, or typical use cases, offering only a basic statement of functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool counts items, implying a read-only operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, output format, or whether it's a safe query. The description is minimal and lacks essential operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and low schema coverage (0%), the description is incomplete. It doesn't provide enough context for an agent to understand how to use the tool effectively, such as parameter usage, return values, or behavioral constraints, making it inadequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one required parameter 'kwargs' of type string. The description adds no meaning beyond the schema—it doesn't explain what 'kwargs' represents, its expected format, or how it relates to counting by MITRE technique. This fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Count') and resource ('Sentinel analytics rule templates by MITRE technique'), providing specific verb+resource. However, it doesn't distinguish itself from the sibling tool 'sentinel_analytics_rules_count_by_technique' which counts rules rather than rule templates, missing explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'sentinel_analytics_rule_templates_list' or 'sentinel_analytics_rules_count_by_technique'. The description lacks context about prerequisites, exclusions, or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't cover critical aspects like pagination, rate limits, authentication requirements, or the format of returned data. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and a parameter with 0% coverage, the description is incomplete. It covers the basic purpose but misses behavioral details, parameter guidance, and output expectations, which are essential for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions no parameters, while the schema has one required parameter ('kwargs') with 0% schema description coverage. This leaves the parameter completely undocumented, failing to compensate for the schema gap and providing no semantic context for what 'kwargs' should contain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'all Sentinel analytics rule templates', which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'sentinel_analytics_rule_template_get' (which retrieves a single template) or 'sentinel_analytics_rule_list' (which lists actual rules, not templates), leaving some ambiguity in the tool ecosystem.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention sibling tools like 'sentinel_analytics_rule_template_get' for single templates or 'sentinel_analytics_rule_list' for actual rules, nor does it specify prerequisites or contexts for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'summarizes' role assignments, implying a read-only operation, but doesn't specify whether it requires specific permissions, what format the summary takes (e.g., structured data, report), or any limitations (e.g., rate limits, data freshness). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality, making it easy to parse quickly. There's no wasted language or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (summarizing RBAC role assignments), lack of annotations, no output schema, and poor parameter documentation (0% coverage with no description compensation), the description is incomplete. It doesn't provide enough context for an agent to understand how to use the tool effectively, what to expect in return, or handle potential errors. The conciseness comes at the cost of necessary details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('kwargs') with 0% schema description coverage, meaning the schema provides no details about what this parameter expects. The description adds no information about parameters—it doesn't mention 'kwargs' or explain what arguments should be passed. With a single undocumented parameter and no compensation in the description, this is inadequate for tool invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Summarize Azure RBAC role assignments for Sentinel and Log Analytics access.' It specifies the verb ('summarize'), resource ('Azure RBAC role assignments'), and scope ('for Sentinel and Log Analytics access'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'sentinel_metadata_get' or 'sentinel_workspace_get', which might also provide authorization-related information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or exclusions. Given the sibling tools include various Sentinel-related tools (e.g., 'sentinel_metadata_get', 'sentinel_workspace_get'), there's no indication of how this tool differs or when it should be preferred over others for authorization-related queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "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 states it 'gets' information, implying a read-only operation, but doesn't specify authentication needs, rate limits, error handling, or what the output looks like. For a tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, 0% schema coverage, no output schema, and a single but undocumented parameter, the description is insufficient. It doesn't compensate for the missing structured data, leaving the agent with inadequate information to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. The agent has no guidance on what 'kwargs' should contain (e.g., domain name, format options), making parameter usage unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('WHOIS information for a domain'), making the purpose immediately understandable. However, it doesn't distinguish this tool from any potential siblings (e.g., other WHOIS-related tools), though none are listed among the provided siblings, so this is a minor gap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention prerequisites, limitations, or related tools, leaving the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the tool counts queries by tactic, implying a read-only aggregation operation, but lacks details on permissions, rate limits, output format, or error handling. For a tool with zero annotation coverage, this is insufficient to guide safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with zero waste, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a counting operation with a parameter), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't cover parameter usage, behavioral context, or output details, leaving significant gaps for the agent to infer or fail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' should contain, its format, or how it influences the count. This leaves the parameter undocumented, failing to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Count Sentinel hunting queries (saved searches) by tactic.' It specifies the verb ('count'), resource ('Sentinel hunting queries'), and grouping dimension ('by tactic'). However, it doesn't explicitly differentiate from siblings like 'sentinel_hunting_queries_list' or 'sentinel_analytics_rules_count_by_tactic,' which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention prerequisites, context, or exclusions, nor does it reference sibling tools like 'sentinel_hunting_queries_list' for listing queries or 'sentinel_analytics_rules_count_by_tactic' for counting analytics rules. This leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Get' which implies a read operation, but doesn't specify whether this requires authentication, rate limits, what format the geolocation data returns, or any error conditions. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and undocumented parameters, the description is insufficient. It covers the basic purpose but lacks crucial details about behavior, parameter usage, and return values that would help an agent use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about the single parameter 'kwargs'. With 0% schema description coverage and no parameter details in the description, the agent has no guidance on what this parameter expects or how to format it. This is inadequate for a tool with one required parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('geolocation data for an IP address'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings, but since none of the sibling tools appear to handle IP geolocation, this is sufficient for clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or constraints. It simply states what the tool does without context about appropriate scenarios or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what details are retrieved (metadata, retention, row count) but lacks critical information such as whether this is a read-only operation, authentication requirements, rate limits, or error handling. The description is insufficient for a mutation-sensitive context without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It uses parentheses to list examples of details concisely, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a tool with 1 undocumented parameter, no annotations, and no output schema, the description is incomplete. It covers the basic purpose but lacks essential details on parameters, behavioral traits, and return values, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. This leaves the parameter completely undocumented, failing to compensate for the schema gap and making it unclear how to invoke the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Get details (metadata, retention, row count, etc.) for a Log Analytics table,' which specifies the verb ('Get'), resource ('Log Analytics table'), and scope of details. However, it doesn't explicitly differentiate from sibling tools like 'sentinel_logs_table_schema_get' or 'sentinel_logs_tables_list,' which reduces clarity in a crowded context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't specify if this is for retrieving metadata versus schema or list operations, nor does it mention prerequisites or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves schema information, implying a read-only operation, but does not cover aspects like authentication requirements, rate limits, error handling, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and efficiently conveys the essential information, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a schema retrieval tool with no annotations, 0% schema description coverage, and no output schema, the description is insufficient. It does not explain the return values, error conditions, or necessary input details, leaving the agent with inadequate information to use the tool effectively in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It does not explain what 'kwargs' should contain (e.g., table name or identifier) or how to format it, failing to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('schema (columns/types) for a Log Analytics table'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'sentinel_logs_table_details_get' or 'sentinel_logs_tables_list', which might have overlapping or related functions, so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'sentinel_logs_table_details_get' or 'sentinel_logs_tables_list', nor does it mention any prerequisites or context for usage. It lacks explicit when/when-not statements or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists tables but doesn't explain what 'available' means, whether it requires authentication, if there are rate limits, or what the output format looks like. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and 1 undocumented parameter, the description is incomplete. It explains what the tool does at a high level but lacks essential details about behavior, parameters, and output that would help an agent use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. The description doesn't mention any parameters at all, failing to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('available tables in the Log Analytics workspace'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'sentinel_logs_table_details_get' or 'sentinel_logs_table_schema_get', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, context, or comparison to sibling tools like 'sentinel_logs_search' or 'sentinel_logs_table_details_get', leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose details like pagination, rate limits, authentication requirements, or what 'all' entails (e.g., completeness, ordering). For a tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to scan and understand quickly. Every part of the sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It covers the basic purpose but lacks parameter details, behavioral context, and output information. For a tool with one parameter and no structured support, more guidance is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. The description doesn't explain what 'kwargs' represents, its format, or how it affects the listing. With low schema coverage, the description fails to compensate, leaving parameters undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all') and resource ('Sentinel ML analytics settings'), with scope ('in the current workspace'). It distinguishes from sibling 'sentinel_ml_analytics_setting_get' by indicating it lists all settings rather than retrieving a single one. However, it doesn't explicitly differentiate from other list tools like 'sentinel_analytics_rule_list' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites, when not to use it, or compare it to other list tools for similar resources (e.g., 'sentinel_analytics_rule_list'). Usage is implied by the resource name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'List all' but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, or what 'current workspace' means. For a list operation with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a parameter with 0% coverage, the description is incomplete. It lacks details on behavior, parameters, return values, and differentiation from siblings, making it insufficient for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. The description doesn't compensate for the lack of schema documentation, leaving the parameter's purpose and usage completely unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all') and resource ('Sentinel source controls in the current workspace'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'sentinel_source_control_get' (singular vs. plural), which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., 'sentinel_source_control_get' for a single source control, or other list tools like 'sentinel_analytics_rule_list'). It only states what it does without context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, requires authentication, has rate limits, or what the output looks like, which is insufficient for a tool with unknown behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for the minimal information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on parameters, behavior, and output, making it inadequate for a tool that likely interacts with threat intelligence data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter information. The single parameter 'kwargs' is undocumented in both schema and description, leaving its meaning and usage completely unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('specific Sentinel threat intelligence indicator'), making the purpose understandable. It doesn't distinguish from siblings like 'sentinel_ti_indicator_metrics_collect', but the specificity is adequate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or differences from related tools like 'sentinel_incident_get' or 'sentinel_hunting_query_get', leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, potential error conditions (e.g., invalid object ID), rate limits, or authentication needs. The description is minimal and doesn't add meaningful context beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, clearly front-loading the core purpose. It's appropriately sized for a simple retrieval tool, though this conciseness comes at the cost of missing details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what information is returned about the group, error handling, or how to structure the parameter. Given the complexity of interacting with Entra ID/Azure AD, more context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description doesn't explain the single parameter 'kwargs'. It mentions 'by object ID' but doesn't clarify how to provide this in 'kwargs' (e.g., format, required fields). The description fails to compensate for the lack of schema documentation, leaving parameter usage ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('a group from Entra ID (Azure AD)'), specifying retrieval by object ID. It distinguishes from sibling 'entra_id_list_groups' by focusing on single-group lookup rather than listing, though it doesn't explicitly mention this distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'entra_id_list_groups' or 'entra_id_get_user', nor any prerequisites such as authentication requirements or access permissions. The description only states what it does without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a 'Get' operation, implying read-only behavior, but doesn't specify whether it requires authentication, has rate limits, what happens if the template doesn't exist, or the format of the returned content. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core purpose and efficiently conveys the essential information without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain what 'raw markdown content' entails, error conditions, or behavioral details needed for reliable use. For a tool with such minimal structured data, more context is required to be fully helpful.
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 for the undocumented parameter. It mentions 'by name', which hints that the parameter is a template name, but doesn't specify format, constraints, or examples. This adds minimal value beyond the schema's generic 'kwargs' parameter, failing to fully address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('raw markdown content for a specific template by name'), making the purpose immediately understandable. It distinguishes from the sibling 'markdown_templates_list' by specifying retrieval of individual content rather than listing. However, it doesn't fully differentiate from other 'get' tools like 'llm_instructions_get' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention prerequisites (e.g., needing a template name), when not to use it, or how it relates to siblings like 'markdown_templates_list' for discovering available templates first. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'Get[s] full details', implying a read-only operation, but doesn't clarify if it requires specific permissions, what 'full details' includes, or any rate limits or error conditions. For a tool with zero annotation coverage, this is a significant gap in transparency about how the tool behaves beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes essential information, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a query retrieval tool with no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It lacks details on behavioral traits, parameter usage, and expected outputs, which are crucial for an AI agent to use this tool effectively in a security context like Sentinel hunting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, meaning the schema provides no semantic information. The description mentions retrieving by 'name or ID', which hints at the parameter's purpose but doesn't specify the exact format (e.g., string input, how to distinguish name vs. ID). This adds minimal value beyond the schema, insufficient to compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'full details of a Sentinel hunting query (saved search)', making the purpose evident. It specifies retrieval by 'name or ID', which adds useful context. However, it doesn't explicitly differentiate from sibling tools like 'sentinel_hunting_queries_list' or 'log_analytics_saved_search_get', which handle similar resources but with different scopes (list vs. single item).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention sibling tools like 'sentinel_hunting_queries_list' for listing queries or 'log_analytics_saved_search_get' for similar saved searches, nor does it specify prerequisites or exclusions. This lack of contextual usage information leaves the agent to infer based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool tests queries with mock data and validates KQL locally, which implies a read-only, non-destructive operation, but doesn't clarify permissions, rate limits, or what 'locally' entails (e.g., no network calls). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.
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 highly concise and front-loaded, consisting of a single sentence that efficiently conveys the core functionality: 'Test a KQL query with mock data using a datatable. Validates KQL locally first.' Every word earns its place, with no wasted text or redundancy, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a query-testing tool with 1 parameter, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on parameter usage, behavioral traits (e.g., error handling, mock data scope), and output format. While concise, it doesn't provide enough context for an agent to use the tool effectively without additional assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' should contain (e.g., the KQL query string, datatable configuration, or validation options). With low schema coverage, the description fails to compensate, leaving the parameter's meaning and usage unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Test a KQL query with mock data using a datatable. Validates KQL locally first.' It specifies the verb ('test'), resource ('KQL query'), and method ('with mock data using a datatable'), making the purpose unambiguous. However, it doesn't explicitly differentiate from its sibling 'sentinel_logs_search' or other query-related tools, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 mentions 'validates KQL locally first,' which implies a testing or validation context, but doesn't specify when to choose this over 'sentinel_logs_search' (for real data) or 'sentinel_query_validate' (for validation without mock data). Without explicit usage context or exclusions, the agent lacks clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states this is a list operation but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, or what 'all' means in practice (e.g., completeness guarantees).
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 wasted words. It's appropriately sized and front-loaded with the essential action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain the parameter, return format, or behavioral constraints, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one undocumented parameter 'kwargs'. The description adds no parameter information beyond what's in the schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all') and resource ('Sentinel metadata'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'sentinel_metadata_get' or explain what 'metadata' specifically refers to in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'sentinel_metadata_get' or other list tools. The description mentions 'current workspace' but doesn't explain prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description lacks behavioral details. It doesn't specify if this is a read-only operation, what permissions are required, error handling, or the response format. The description only states the action without behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core action, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, 0% schema coverage, and no output schema, the description is insufficient. It doesn't cover parameter details, behavioral traits, or usage context, leaving significant gaps for an AI agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description mentions 'by name' but doesn't explain the 'kwargs' parameter's format or usage. It adds minimal semantics beyond the schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('a specific Sentinel ML analytics setting'), making the purpose evident. However, it doesn't differentiate from its sibling 'sentinel_ml_analytics_settings_list', which retrieves multiple settings instead of one by name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention the sibling 'sentinel_ml_analytics_settings_list' for listing all settings or prerequisites like authentication needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'locally' which implies no network call or resource consumption, but doesn't disclose what validation entails (syntax checking, semantic validation, performance estimation), what errors might be returned, or whether this affects any system state. For a validation tool with zero annotation coverage, this is insufficient behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 5 words. It's front-loaded with the core purpose and wastes no words. Every word earns its place by conveying essential information about what the tool does and its scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's apparent simplicity (single parameter, no output schema), the description is incomplete. It doesn't explain what constitutes valid KQL syntax, what the validation output looks like, or how this differs from executing queries. With no annotations and minimal parameter documentation, the description should provide more context about the tool's behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about the single parameter 'kwargs'. With 0% schema description coverage and no parameter details in the description, the agent has no guidance on what to pass. The description doesn't compensate for the schema's lack of documentation, leaving the parameter's purpose and format completely unspecified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Validate KQL Query Syntax locally'. It specifies the verb (validate), resource (KQL Query Syntax), and scope (locally). However, it doesn't differentiate from sibling tools like 'sentinel_logs_search' which might also involve KQL queries but for different 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 doesn't mention prerequisites, when validation is needed, or what happens after validation. With many sibling tools for Sentinel operations, this lack of context leaves the agent guessing about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't mention any constraints like pagination, rate limits, authentication requirements, or what 'all items' entails (e.g., if there are limits). This leaves significant gaps for a tool with one parameter.
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 wasted words. It's front-loaded with the core action and resource, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and a parameter with 0% schema coverage, the description is incomplete. It covers the basic purpose but lacks details on usage, parameters, behavioral traits, or return values, which are critical for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. The description doesn't explain what 'kwargs' should contain (e.g., watchlist identifier, filters) or its format, failing to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('items in a Sentinel watchlist'), making the purpose unambiguous. It doesn't explicitly differentiate from sibling tools like 'sentinel_watchlist_get' or 'sentinel_watchlist_item_get', but the focus on 'items' provides some implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'sentinel_watchlist_get' (which might retrieve watchlist metadata) or 'sentinel_watchlist_item_get' (which might retrieve a specific item). The description lacks context about prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns raw markdown but doesn't cover critical aspects like error handling, rate limits, authentication needs, or what happens if the path is invalid. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every part contributing essential information, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and low parameter coverage, the description is incomplete. It lacks details on return values, error cases, and behavioral traits, making it inadequate for an agent to fully understand how to use this tool effectively in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description doesn't add any semantic details about the 'kwargs' parameter. It fails to explain what 'documentation path' means, its format, or examples, leaving the parameter's meaning unclear and not compensating for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Return') and resource ('raw markdown for a given documentation path'), making the purpose specific and understandable. However, it doesn't distinguish this tool from its sibling 'tool_docs_list' or 'tool_docs_search', which appear to be related documentation tools, so it misses full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'tool_docs_list' or 'tool_docs_search'. It lacks context about prerequisites, exclusions, or specific scenarios, leaving the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions enumeration but fails to specify whether this is a read-only operation, if it requires authentication, what the output format is, or any rate limits. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the core purpose. There is no wasted verbiage, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (one parameter with 0% schema coverage, no annotations, and no output schema), the description is incomplete. It lacks details on parameters, behavioral traits, and output, making it insufficient for effective agent use without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the single parameter 'kwargs'. It provides no meaning beyond the schema, failing to compensate for the lack of schema documentation, which is inadequate for a tool with one required parameter.
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 ('Enumerate') and resource ('available Sentinel server documentation markdown paths'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'tool_docs_get' or 'tool_docs_search', which appear related to documentation access but serve different 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?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, timing, or comparisons to sibling tools such as 'tool_docs_get' or 'tool_docs_search', leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the action ('search') and output ('matching paths'), but lacks details on permissions, rate limits, search scope, result format, or error handling. For a search tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—just one sentence with two clauses. It's front-loaded with the core functionality and wastes no words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and minimal parameter information, the description is incomplete. It doesn't cover behavioral aspects like search behavior, result limitations, or error cases, which are critical for a search tool. The context signals show significant gaps in documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 1 parameter with 0% description coverage, and the tool description provides no information about the 'kwargs' parameter. It doesn't explain what 'kwargs' should contain (e.g., search query, filters) or its format, leaving the parameter's meaning and usage unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Full-text search across documentation; returns matching paths.' It specifies the verb ('search'), resource ('documentation'), and output format ('matching paths'). However, it doesn't differentiate from its sibling 'tool_docs_get' and 'tool_docs_list', which also work with documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 doesn't mention sibling tools like 'tool_docs_get' (for retrieving specific documentation) or 'tool_docs_list' (for listing documentation), nor does it specify scenarios where full-text search is preferred over other methods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic operation. It doesn't disclose whether this is a read-only operation, pagination behavior, rate limits, authentication requirements, or what format the results return. The description adds minimal behavioral context beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word contributes to understanding the tool's function without any redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, 0% schema coverage, and no output schema, the description is insufficient. It doesn't explain the single required parameter's usage, return format, behavioral constraints, or how it differs from related hunting query tools. The description leaves too many gaps for effective agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% with 1 required parameter ('kwargs'), but the description only mentions 'optional tactic/technique filtering' without explaining how to use the kwargs parameter for this filtering. The description fails to compensate for the complete lack of schema documentation, leaving the parameter's purpose and format unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all') and resource ('Sentinel hunting queries/saved searches') with optional filtering capability. It distinguishes from siblings like sentinel_hunting_query_get (singular) and sentinel_hunting_queries_count_by_tactic (counts rather than lists), but doesn't explicitly mention these distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'optional tactic/technique filtering' but doesn't explicitly state when to use this tool versus alternatives like sentinel_hunting_queries_count_by_tactic or sentinel_hunting_query_get. No guidance on prerequisites, limitations, or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions retrieval but doesn't disclose behavioral traits like authentication needs, rate limits, response format, or potential side effects. The guidance to use it first hints at initialization, but lacks detail on what the instructions contain or how they affect subsequent tool usage.
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 sentences with zero waste. It's front-loaded with the purpose and followed by usage guidance, making it highly efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, no output schema, and a parameter-heavy context (1 required param), the description is incomplete. It lacks details on parameters, return values, and behavioral aspects, making it insufficient for an agent to use the tool effectively beyond the high-level guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about the single required parameter 'kwargs'. It doesn't explain what 'kwargs' represents, its format, or how it should be used, leaving the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'retrieve' and the resource 'LLM usage instructions for the Sentinel MCP Server'. It specifies what the tool does, though it doesn't explicitly differentiate from sibling tools, which are unrelated to LLM instructions.
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 explicitly states 'Use this tool first before all other tools', providing clear when-to-use guidance. It implies this is a prerequisite for other operations, though it doesn't name specific alternatives or exclusions.
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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