GitIntel

by hoangsonww

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct aspect of git analytics such as churn, coupling, contributor stats, and code age, with no functional overlap.
Naming Consistency5/5
All tool names are descriptive nouns or noun compounds in lowercase snake_case, following a consistent pattern (e.g., knowledge_map, commit_patterns).
Tool Count5/5
12 tools is well-scoped for a git intelligence server, covering analysis, risk, history, and collaboration without being overwhelming.
Completeness5/5
The toolset comprehensively covers code metrics, change patterns, ownership, risk, and history, with no obvious gaps for typical git analysis tasks.
Average 4.2/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on March 5, 2026
- 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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the description carries a lower burden. It adds context about what the analysis covers (stale, diverged, merge-risk branches) and the repo_path condition. No contradictions.
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 lean and front-loaded: first sentence summarizes the tool, second expands on findings, third is a conditional note. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could detail the return format, but it clearly states what the tool identifies. Annotations cover safety, and parameters are well-documented in schema. Slightly incomplete on output, but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal parameter info beyond the schema (only repeats the repo_path condition). No added value for base_branch or include_remote.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Analyze', 'Identifies') and clearly states the resource ('all branches'). It covers staleness, divergence, and merge risk, which distinguishes it from sibling tools like 'hotspots' or 'churn'.
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 includes a conditional guideline about repo_path, but does not explicitly compare to sibling tools or state when to use this tool over others (e.g., 'risk_assessment'). Usage is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description's 'Analyze' is consistent. It adds context about interpreting churn as a red flag and the git requirement, but does not disclose other behavioral traits like authorization needs or rate limits. Given annotations, the added value is moderate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with purpose, and each sentence serves a clear role: definition, interpretation, and usage note. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only analysis tool with 4 well-described parameters and annotations, the description covers the concept and a key requirement. Lack of output schema is noted, but the description is sufficient to guide 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 coverage is 100%, so the baseline is 3. The description mentions the 'repo_path' requirement specifically, but does not add semantics beyond the schema for other parameters. The schema descriptions already cover the parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the resource ('code churn') and verb ('Analyze'), and provides a concrete example ('500 lines added and 400 deleted') that illustrates the concept. It effectively distinguishes the tool from its many siblings by focusing on churn measurement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (high churn indicates instability) and includes a critical prerequisite: providing 'repo_path' if outside a git repo. However, it does not offer alternatives among sibling tools or explicitly state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the agent knows it is safe. The description adds valuable context about the analysis performed and specific patterns revealed (weekend deployments, late-night hotfixes, declining velocity), enhancing transparency beyond 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?
Two sentences, front-loaded with key analysis types, followed by examples and a conditional note. Every sentence adds value, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the output in terms of distributions, heatmaps, breakdowns, and trends. It also covers the conditional requirement for repo_path. Misses explicit mention of return format (e.g., table or chart), but sufficient for selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with adequate descriptions for all three parameters. The description does not add significant meaning beyond the schema, aside from giving examples of output patterns. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes commit patterns including day-of-week distribution, hour-of-day heatmap, commit size breakdown, and weekly velocity trends, and distinguishes from sibling tools like hotspots, churn, etc. by focusing on temporal and size-based analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a specific note about requiring repo_path if the server wasn't started in a git repo, but doesn't explicitly state when to use this tool vs alternatives like contributor_stats or file_history. Usage context is implied but not differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and description adds important behavioral context: the requirement for repo_path if not in a git repo, and the defect correlation insight. No contradiction.
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?
Three concise sentences. Front-loads the core purpose, adds rationale, and ends with a critical usage condition. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Provides clear purpose, usage condition, and defect correlation context. No output schema exists, but description omits what the output looks like. Otherwise complete for a read-only listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 4 parameters with descriptions (100% coverage). Description only adds a conditional note on repo_path; does not significantly augment parameter meaning beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Find' and resource 'files that change most frequently', clearly distinguishing from siblings like churn and coupling. Adds context about defect correlation and actionable use.
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?
States to use for identifying files needing refactoring, but lacks explicit guidance on when not to use or alternatives among siblings. The repo_path condition is helpful but no comparison to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations confirm readOnlyHint=true, and description aligns with a non-destructive, analytical tool. Description adds value by detailing combined signals and return format (score, per-file breakdown, recommendations). No contradictions.
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?
Two concise sentences plus a note. Front-loaded with main purpose and key details. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description adequately explains return values (score, breakdown, recommendations). Covers essential context for usage, including default behavior and prerequisite for repo_path.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions. The tool description adds context: default behavior (uncommitted changes) and condition for repo_path (required if not in git repo). This enhances understanding 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?
Clearly states it assesses risk profile of uncommitted changes or a commit range. The verb 'assess' and resource 'risk profile' are specific. However, it does not explicitly differentiate from sibling tools like hotspots or churn, which may overlap in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a conditional usage note about repo_path when server is not in a git repo. But it lacks guidance on when to use this tool vs alternatives, such as when to prefer risk_assessment over hotspots or branch_risk.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, and the description does not contradict this. It adds behavioral context: it samples at regular intervals, identifies spikes, etc. No mention of destructive effects or permissions needed, but given readOnlyHint, the description sufficiently supplements the annotation.
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 sentences plus a crucial note, all front-loaded with purpose and benefits. Every sentence earns its place with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks specifics about the return value or output format, and there is no output schema. While the tool's purpose and usage are clear, a user (or AI) might need to know what kind of data the trend provides (e.g., numeric values, charts?). This is a minor gap.
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?
All parameters have descriptions in the input schema (100% coverage), so the baseline is 3. The description does not add extra semantics beyond the schema, such as format or constraints not already mentioned.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tracks how a file's complexity has changed over time via git history sampling. The specific verb 'track' and resource 'file complexity' are present, and the focus on trends distinguishes it from sibling tools like 'hotspots' which likely give a single snapshot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly details what the tool identifies: files growing out of control, complexity spikes from specific commits, and files needing splitting. It also provides a prerequisite note about repo_path when not in a git repo. However, it lacks explicit when-not-to-use guidance or direct 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the description adds value by explaining the concept of temporal coupling and giving a concrete example (auth.ts and middleware.ts). This context helps the agent understand the tool's output and significance.
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 relatively concise with minimal waste. The example and note are useful, but the explanation of temporal coupling could be slightly tighter. Good front-loading of purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data analysis tool with no output schema, the description adequately conveys what to expect (file pairs with coupling score). Parameters are well-covered in schema. Could mention results format briefly, but overall complete.
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 all parameters are documented. The description only adds the note about repo_path, which is already in the schema. No additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds files that always change together (temporal coupling), with a specific verb and resource. It distinguishes itself from sibling tools by focusing on hidden dependencies not visible in imports or type signatures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (to find hidden dependencies) and includes a critical note about providing repo_path if not in a git repo. However, it does not explicitly contrast with sibling tools or give when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description reinforces this by describing a read-only analysis (showing age, identifying stale files). It adds behavioral context about identifying potential dead code and abandoned features. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3 sentences) and front-loaded with the core purpose. Each sentence adds value: purpose, utility, and a critical note. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, no output schema, and moderate complexity, the description adequately explains the tool's purpose and context. However, it does not describe the return format (e.g., list with file paths and dates), which would help agents understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 4 parameters have descriptions). The description adds use-case context but does not provide additional parameter-level details beyond what the schema already covers. Baseline score of 3 is appropriate as the description does not compensate for missing schema info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool shows the age of code in each file (last modified time) and identifies stale files. It uses specific verbs ('Show', 'Identifies') and distinguishes from sibling tools by focusing on file age rather than hotspots, churn, or other analyses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: cleanup planning, onboarding, understanding evolving areas. It also includes a conditional note about requiring repo_path when not inside a git repo. However, it does not explicitly compare to siblings or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so no safety contradiction. The description discloses the weighting algorithm and the requirement for repo_path, providing useful behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three efficient sentences that front-load the purpose, then usage, then a critical note. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output format description, but use cases and constraints are well-covered. For a read-only query tool, this is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds the note about repo_path but does not elaborate on days or path beyond what the schema already provides. No semantic gap, but also no added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool identifies who knows a file/directory best, using specific weighting criteria (recency, volume, commit frequency). It then lists concrete use cases (reviewer, silos, transitions), fully distinguishing it from sibling tools like hotspots or churn.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit use cases and a crucial prerequisite (provide repo_path if not in a git repo). It does not contrast directly with siblings, but the use cases imply when to choose this tool over alternatives like coupling or contributor_stats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds value by detailing the scope of analytics and the collaboration graph aspect. No contradictions.
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?
Two concise sentences plus a note, front-loaded with purpose. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 simple params, no output schema, and good annotations, the description covers purpose, usage, and a key prerequisite. Missing return format details but acceptable given no output schema.
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?
All 3 parameters are described in the schema (100% coverage). The description adds a redundant note about repo_path but doesn't clarify days or author beyond schema defaults. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides 'comprehensive contributor analytics' including specific aspects like activity, areas, commit patterns, and collaboration graph. It effectively distinguishes from sibling tools (e.g., hotspots, churn) by focusing on people rather than code or risk.
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 when to use this tool (understanding team dynamics, knowledge silos, onboarding, workload distribution) and provides a critical prerequisite note about repo_path if not in a git repo. No exclusions, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=false, which the description does not contradict. The description adds valuable behavioral detail: 'Uses --follow to track renames.' This goes beyond annotations and helps the agent understand renames handling.
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 sentences plus a note, front-loaded with the primary action and use cases. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, but the description gives a high-level idea of output fields (who, when, how much, why). It covers prerequisites and behavior. A more detailed output description would be beneficial, but overall it is sufficiently complete for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds a behavioral note about --follow, which relates to path handling, but does not provide additional parameter-level semantics beyond what the schema offers. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool shows the full commit history of a specific file, with details on who changed it, when, how much, and why. It distinguishes from sibling tools (e.g., hotspots, churn) by focusing specifically on file commit history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases (understanding file evolution, bug introduction, module tracing) and a prerequisite (require repo_path if not in git repo). However, it does not mention when not to use this tool or alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only indicate readOnlyHint=true. The description adds behavioral context: it generates release notes by grouping, extracting breaking changes, and linking PR/issue references. This goes beyond the annotation to explain what processing occurs, though it could detail more about output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences plus a note. The main action is front-loaded, the capabilities are listed succinctly, and the critical usage condition is highlighted as a note. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters (1 required) and no output schema, the description covers the core functionality and a key usage condition. It lacks explicit mention of return format, but the purpose is clear enough. Sibling tools are all different analyses, so no confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for each parameter. The description adds value by explaining the grouping behavior (conventional commit type) and the condition for repo_path. It also clarifies that grouping can be by type, scope, or author, which aligns with the enum but provides functional context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates structured release notes from commits between two git refs, groups by conventional commit type, extracts breaking changes, and links references. This specific verb-resource pair distinguishes it from sibling tools that analyze code hotspots, churn, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides a usage note about when repo_path is required ('If the server was not started inside a git repo, you MUST provide repo_path'). It does not give when-not-to-use or alternatives, but the context is clear enough for an agent to decide when to invoke this tool.
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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