CastPlan MCP

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 with clear boundaries, such as docs_search for searching and docs_update for updating. However, some overlap exists between analyze_document_quality and generate_documentation_report, as both involve quality assessment, which could cause minor confusion.
Naming Consistency4/5
The naming follows a consistent snake_case pattern throughout, with clear verb_noun structures like docs_search and hooks_setup_git. A minor deviation is bmad_parse_specification, which uses a prefix (bmad) that breaks the pure verb_noun flow, but overall it remains readable and predictable.
Tool Count4/5
With 16 tools, the count is slightly high but reasonable for a documentation automation system, covering areas like document management, hooks, and analysis. It might feel a bit heavy, but each tool appears to serve a specific function without obvious redundancy.
Completeness5/5
The tool set provides comprehensive coverage for documentation automation, including CRUD-like operations (search, update, validate), lifecycle management (update_document_lifecycle), analysis (analyze_document_quality), and automation hooks (setup, trigger). No significant gaps are apparent for this domain.
Average 2.9/5 across 16 of 16 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- No commit activity data available
- Last stable release on July 31, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Find and reference' but doesn't explain what 'reference' entails (e.g., does it return links, copy text, or something else?), whether it requires authentication, has rate limits, or what the output looks like. For a tool with no annotations, this leaves critical behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse, though it could be slightly more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what the tool returns, how it interacts with parameters, or behavioral aspects like error handling. For a tool that likely outputs documentation references, the lack of output details and behavioral context makes it inadequate for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no meaning beyond what the schema provides—it doesn't explain how parameters like 'files' or 'context' influence the tool's behavior or relate to finding documentation. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't enhance parameter understanding.
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 'Find and reference relevant documentation for development work' states a clear purpose with a verb ('Find and reference') and resource ('documentation'), but it's vague about what 'reference' means and doesn't distinguish this tool from sibling tools like 'docs_search' or 'generate_documentation_report'. It provides a general function without specificity about how it differs from other documentation-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives like 'docs_search' or 'generate_documentation_report'. It lacks explicit when/when-not instructions or mentions of prerequisites, leaving the agent to infer usage based on the tool name and parameters alone, which is insufficient for effective tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but lacks behavioral details. It doesn't disclose if initialization is idempotent, requires specific permissions, has side effects (e.g., creating files), or involves network calls. The term 'enhanced' hints at features but doesn't clarify behavior, leaving critical operational traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without fluff. It's front-loaded and appropriately sized, though it could be more specific to improve clarity without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of initializing a system with 4 parameters and no annotations or output schema, the description is incomplete. It doesn't cover expected outcomes, error conditions, or how it integrates with sibling tools, leaving gaps in understanding the tool's full context and operational impact.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing clear parameter documentation. The description adds no additional meaning beyond the schema, such as explaining interactions between parameters (e.g., how 'enableAI' affects initialization) or usage examples. Baseline 3 is appropriate as the schema handles parameter semantics adequately.
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 ('initialize') and target ('enhanced documentation automation system for a project'), which is clear but vague. It doesn't specify what 'initialize' entails (e.g., setup, configuration, activation) or differentiate from siblings like 'hooks_setup_git' or 'track_document_work', leaving ambiguity about its specific role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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., project setup), exclusions, or related tools like 'generate_documentation_report' or 'docs_update', leaving the agent to infer usage context without explicit 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. While 'perform comprehensive quality analysis' implies a read-only operation, it doesn't specify whether this tool modifies the document, requires specific permissions, has rate limits, or what the output format looks like. The mention of 'AI insights' hints at computational intensity but lacks concrete behavioral details needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 front-loaded with the core action and resource, making it easy to parse. Every part of the sentence ('comprehensive quality analysis,' 'documentation,' 'AI insights') contributes to understanding 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 the complexity of a 3-parameter tool with no annotations and no output schema, the description is inadequate. It doesn't explain what the analysis returns, how results are structured, or any behavioral constraints. While the schema covers parameters, the overall context for using this tool—especially alongside siblings like 'docs_validate'—is missing, leaving significant gaps for an agent to operate effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema—it doesn't explain how 'documentPath' should be formatted, what 'AI-powered analysis' entails, or how 'analysisTypes' interact. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.
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 ('Perform comprehensive quality analysis') and the resource ('documentation'), making the purpose understandable. It adds 'with AI insights' which provides additional context about the approach. However, it doesn't explicitly differentiate this from sibling tools like 'docs_validate' or 'generate_documentation_report', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 sibling tools like 'docs_validate' and 'generate_documentation_report' that might handle similar tasks, there's no indication of when this specific analysis tool is preferred, what prerequisites exist, or any exclusions. This leaves the agent to guess 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. It mentions parsing and task generation but doesn't disclose behavioral traits such as whether this is a read-only operation, if it modifies data, error handling, performance characteristics, or side effects. For a tool with 5 parameters and no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Parse a business specification document and generate tasks.' It's front-loaded with the core purpose and has zero waste, making it easy to 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 (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the tool returns, how tasks are generated, or any behavioral context. For a parsing and generation tool, more detail is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what's in the schema, such as explaining the relationship between parameters or providing usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.
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: 'Parse a business specification document and generate tasks.' It specifies the verb ('parse') and resource ('business specification document'), and mentions the output ('generate tasks'). However, it doesn't distinguish this from sibling tools like 'analyze_document_quality' or 'generate_documentation_report', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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. With siblings like 'analyze_document_quality' and 'generate_documentation_report', there's no indication of how this tool differs or when it's preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "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 'Update' implies a mutation, but doesn't cover permissions, side effects, error handling, or response format. For a mutation tool with zero annotation coverage, this is inadequate, as it 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 any wasted 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 tool is a mutation (updating task status) with no annotations and no output schema, the description is incomplete. It doesn't explain what happens on success or failure, any constraints on status transitions, or how it integrates with sibling tools like 'track_document_work'. For a 2-parameter mutation tool, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add meaning beyond the input schema, which has 100% coverage with clear descriptions and an enum for 'status'. Since schema_description_coverage is high, the baseline is 3, as the schema adequately documents the parameters without needing extra explanation in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update') and resource ('status of a specific task'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling tools that might also update task properties, like 'track_document_work' or 'update_document_lifecycle', which could involve task status changes in some contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 the task must exist or be in a certain state. Given the sibling tools include 'track_document_work' and 'update_document_lifecycle', which might overlap with task management, this lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Search through project documentation' implies a read-only operation but doesn't specify what gets returned (full documents, snippets, metadata), whether there are rate limits, authentication requirements, or how results are ranked/formatted. This leaves significant behavioral questions unanswered.
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 simple search tool and front-loads the essential information 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?
For a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format results come in, whether there are limitations (like maximum results), or how the search works (full-text, keyword, etc.). Given the lack of structured data elsewhere, the description should provide more operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the single 'query' parameter well-documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides ('Search query to find relevant documentation'), so it meets the baseline for adequate but unenhanced parameter 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 ('Search') and resource ('project documentation'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling search tools like 'docs_reference' or 'get_document_tree', which might also involve finding documentation content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 siblings like 'docs_reference', 'get_document_tree', and 'analyze_document_quality' that might also help find documentation information, there's no indication of when this search function is preferred or what specific use cases it addresses.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions validation but doesn't describe what the tool does operationally (e.g., checks syntax, verifies links, outputs a report), whether it's read-only or has side effects, or any performance or error-handling traits. 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 phrase ('Validate documentation structure and completeness') with no wasted words. It's front-loaded and appropriately sized for its 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 complexity implied by validation tasks, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'validate' entails, what the output might be (e.g., a report, status), or how it fits with siblings, leaving the agent under-informed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter details, and it doesn't contradict the schema. A baseline of 4 is appropriate for a parameterless tool with complete 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 'Validate documentation structure and completeness' states a general purpose (validation) but lacks specificity about what resource it validates (e.g., which documentation) and how it differs from siblings like 'analyze_document_quality' or 'generate_documentation_report'. It's vague about scope and method.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'analyze_document_quality' or 'generate_documentation_report'. The description implies validation but doesn't specify context, prerequisites, or exclusions, leaving the agent without 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. While 'generate comprehensive reports' implies a read-only operation that produces output, it doesn't specify whether this is a long-running process, what permissions are required, what format the report takes, or whether there are rate limits. For a tool with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for the tool's complexity, though it could be slightly more front-loaded with key differentiators if they existed.
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 multiple sibling tools, the description is incomplete. It doesn't explain what the generated report contains, how it's delivered, or how it differs from other documentation analysis tools. For a report generation tool with behavioral unknowns, this leaves too many contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting all three parameters (reportType with enum values, timeRange with start/end dates, includeAI with default). The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 for high 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 'generate' and the resource 'comprehensive reports on documentation status and quality', making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'analyze_document_quality' or 'track_document_work', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 documentation-related sibling tools available (e.g., analyze_document_quality, docs_search, track_document_work), there's no indication of what makes this tool distinct or when it should be preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose whether this requires specific permissions, how events are triggered, what happens if watching is already active, or any rate limits. For a monitoring 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 a single, efficient sentence that front-loads the core action. Every word contributes to understanding the tool's purpose without any wasted text.
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 and no output schema, the description is incomplete for a tool that initiates system monitoring. It lacks details on what events are triggered, how to handle them, error conditions, or interaction with other hooks tools, 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'patterns' documented as optional file patterns to watch. The description adds no additional parameter semantics beyond what the schema provides, so baseline 3 is appropriate.
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 'Start' and the resource 'file system watching', specifying it's for 'automatic event triggering'. It distinguishes from sibling 'hooks_stop_watching' by indicating the opposite action, but doesn't differentiate from other hooks tools like 'hooks_trigger' in terms of when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like 'hooks_trigger' or 'hooks_stop_watching'. The description implies it's for initiating monitoring, but lacks context about prerequisites, timing, or comparisons with 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 full burden for behavioral disclosure. It states the tool triggers events but doesn't explain effects (e.g., whether it executes hooks, modifies state, or requires permissions). This is inadequate for a mutation 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 zero waste. It's front-loaded and appropriately sized for the tool's complexity, earning a high score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (triggering events with data payloads), no annotations, and no output schema, the description is incomplete. It fails to explain what happens after triggering (e.g., hook execution, response format, or error handling), leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (eventType with enum values and data as an object). The description adds no additional meaning beyond what the schema provides, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Trigger a hook event manually' clearly states the action (trigger) and resource (hook event), with 'manually' adding specificity. However, it doesn't distinguish this tool from sibling tools like hooks_start_watching or hooks_stop_watching, which prevents 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 hooks_start_watching or hooks_stop_watching. It lacks context about prerequisites, timing, or exclusions, leaving usage unclear beyond the basic action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Track' suggests a read-only or monitoring operation, but the description doesn't clarify whether this creates records, updates existing ones, or merely logs information. It also omits details like authentication needs, rate limits, or what the tool actually returns (since there's no output schema). For a tool with 4 parameters and no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 for an agent to parse quickly. Every part of the sentence earns its place by conveying 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?
Given the complexity (4 parameters, no annotations, no output schema, and 15 sibling tools), the description is incomplete. It doesn't explain what the tool returns, how it differs from siblings, or the behavioral implications of 'tracking' (e.g., whether it's idempotent or has side effects). For a tool in this context, more detail is needed to guide effective agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no additional meaning about the parameters beyond what's in the schema (e.g., it doesn't explain how 'workType' relates to 'expectedDocuments' or provide examples). With high schema coverage, the baseline score is 3, as the description doesn't need to compensate but also doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Track the relationship between development work and documentation requirements.' It specifies the verb ('track') and the resource ('relationship between development work and documentation requirements'), which is more specific than just restating the name. However, it doesn't explicitly distinguish this tool from its many siblings (e.g., docs_update, generate_documentation_report), 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. With 15 sibling tools on the server (including docs_update, generate_documentation_report, and update_document_lifecycle), there's no indication of when tracking relationships is appropriate versus updating documents directly or generating reports. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a mutation operation ('update') and hints at scheduling, but fails to cover critical aspects such as required permissions, whether changes are reversible, error handling, or rate limits. This leaves significant gaps for a tool that modifies document states.
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 ('update the lifecycle state') and includes a key feature ('optional review scheduling') without any wasted words. It is appropriately sized and structured for quick comprehension.
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 updating document lifecycle states, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral traits, error cases, return values, and how it integrates with sibling tools, making it incomplete 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal value beyond the input schema, which has 100% coverage with clear descriptions for all parameters. It mentions 'optional review scheduling', aligning with the 'scheduledReview' parameter, but does not provide additional context like format details or usage examples. The baseline score of 3 reflects adequate but not enhanced parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and the resource 'lifecycle state of a document', specifying the action and target. However, it does not explicitly distinguish this tool from sibling tools like 'docs_update', which might handle general document updates, leaving some ambiguity in 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 mentions 'optional review scheduling', implying usage for review-related states, but provides no explicit guidance on when to use this tool versus alternatives like 'docs_update' or 'track_document_work'. There are no prerequisites, exclusions, or named alternatives stated, resulting in 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 full burden for behavioral disclosure. It states this is an update operation (implying mutation) but doesn't address permissions, side effects, error handling, or what 'update' entails (e.g., overwriting, appending, versioning). For a mutation 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 states the core purpose without waste. It's appropriately sized for a tool with good schema coverage and no complex behavioral nuances to explain.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with full schema coverage but no annotations or output schema, the description is minimally adequate. It states the purpose but lacks behavioral context (e.g., mutation implications) and doesn't leverage the rich sibling tool context to guide usage. For a mutation tool in a crowded namespace, it should do more.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema (e.g., no examples, no clarification on 'files' format or 'context' content). Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('Update documentation') and context ('after completing development work'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'docs_reference', 'docs_validate', or 'update_document_lifecycle', which likely have overlapping documentation-related 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 minimal contextual guidance ('after completing development work') but offers no explicit when-to-use rules, no exclusions, and no alternatives among the many sibling documentation tools. Without this, an agent might struggle to choose between this and similar tools like 'docs_validate' or 'update_document_lifecycle'.
Agents often have multiple tools that could apply. Explicit usage guidance like "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 'retrieve' but doesn't clarify if this is a read-only operation, potential side effects (e.g., caching), performance considerations, or error handling. 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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and every word earns its place, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a retrieval tool with 3 parameters), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but lacks details on behavior, usage context, and output format, which are crucial for effective tool invocation in this scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents all three parameters with descriptions and defaults. The description adds no additional meaning beyond implying hierarchical retrieval, which aligns with the schema but doesn't provide extra context like examples or edge cases. Baseline 3 is appropriate when the schema does the heavy lifting.
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 'hierarchical document tree structure', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'docs_search' or 'docs_reference', which might also retrieve document-related information but with different scopes or formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 retrieval (e.g., after initialization), or compare it to siblings like 'docs_search' for searching versus 'get_document_tree' for hierarchical views, 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 the full burden of behavioral disclosure. It states the action ('stop') but doesn't explain what happens after stopping (e.g., whether it's reversible, if it affects other operations, or what the response looks like). For a mutation 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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately clear. Every word earns its place, and there's no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation to stop an active process) and the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, success indicators, or error conditions. For a tool that likely changes system state, more context is needed for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce unnecessary complexity.
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 'Stop file system watching' clearly states the action (stop) and the resource (file system watching), making the purpose immediately understandable. It distinguishes from siblings like 'hooks_start_watching' by indicating the opposite operation. However, it doesn't specify what exactly is being stopped (e.g., a specific watcher or all watchers), 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 doesn't mention prerequisites (e.g., that file system watching must be active first), exclusions, or related tools like 'hooks_start_watching' for starting the process. This lack of context leaves the agent guessing about proper 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool sets up Git hooks but does not explain what that entails—e.g., whether it modifies existing hooks, requires specific permissions, or has side effects like overwriting files. For a tool that likely modifies system configurations, this lack of detail is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and every part ('Setup Git hooks for automated documentation and validation') contributes 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters and no output schema, the description is adequate for a basic setup tool. However, it lacks details on behavioral aspects (e.g., what hooks are created, any dependencies) and does not reference sibling tools, leaving gaps in understanding the full context. It meets minimum viability but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the purpose ('for automated documentation and validation'), which goes beyond the schema. However, it does not provide additional context like hook types or validation rules, keeping it from a perfect score.
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: 'Setup Git hooks for automated documentation and validation.' It specifies the verb ('Setup'), resource ('Git hooks'), and intended outcome ('for automated documentation and validation'), making it easy to understand what the tool does. However, it does not explicitly differentiate from sibling tools like 'hooks_start_watching' or 'hooks_trigger', which prevents 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. It does not mention prerequisites (e.g., whether Git is initialized), exclusions, or related tools like 'hooks_start_watching' for ongoing monitoring. Without any usage context, 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.

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