Git MCP Server

Server Quality Checklist

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

Latest release: v0.2.3
Disambiguation4/5
Most tools have distinct purposes targeting specific resources and actions, but some potential overlap exists between get_file_contents and get_repository_tree for file/directory listing, and between create_comment and list_comments for comment-related operations. Descriptions help clarify boundaries, but an agent might occasionally need to choose between similar tools.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with clear, descriptive names. The naming convention is uniform throughout the set, using snake_case consistently and predictable verb choices like create, get, list, update, merge, push, and search.
Tool Count3/5
With 23 tools, the count is on the higher side for a Git server, bordering on heavy. While the tools cover a broad range of Git and CI/CD operations, some might be considered specialized or redundant, making the surface feel slightly bloated compared to a more minimal set.
Completeness5/5
The tool set provides comprehensive coverage for Git operations, including repository management, branching, issues, pull requests, CI/CD pipelines, and file operations. It supports full CRUD/lifecycle workflows for key resources like issues and pull requests, with no obvious gaps that would hinder agent functionality.
Average 3/5 across 23 of 23 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool adds a comment, implying a write operation, but doesn't cover permissions required, rate limits, whether the comment is editable/deletable, or response format. This is inadequate for a mutation tool without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., permissions, side effects), response format, and usage context, leaving significant gaps in understanding how to properly invoke and interpret results from this 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 fully documents all four parameters. The description adds no additional parameter semantics beyond implying the tool operates on issues or pull requests, which is already covered by the 'type' parameter's enum. This meets the baseline 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 action ('Add a comment') and target resources ('to an issue or pull request'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'list_comments' or 'update_issue', which would require explicit comparison to achieve 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?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an existing issue/PR), exclusions, or comparisons to similar tools like 'update_issue' for modifying comments, leaving the agent without contextual usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates an issue but doesn't mention permissions required, whether it's idempotent, error handling, or what happens on success/failure. For a mutation tool, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, 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?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation (e.g., returns issue ID, success status), error conditions, or authentication requirements, leaving the agent with incomplete 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?
The input schema has 100% description coverage, providing clear documentation for all 5 parameters. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3 but 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 action ('Create') and resource ('new issue in a project'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'create_comment' or 'create_pull_request' beyond the obvious resource difference, missing explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'update_issue' or 'list_issues', nor does it mention prerequisites such as authentication or project access. It's a basic statement of function without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action ('create') but doesn't disclose permissions needed, whether creation is reversible, rate limits, error conditions, or what happens on success (e.g., returns PR ID). For a mutation tool with zero annotation coverage, this leaves critical gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and includes only essential clarifying information (the GitLab terminology note). Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 9 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what happens after creation (e.g., returns a PR object/ID), error handling, or system behavior. The agent lacks critical context needed to use this tool effectively despite the comprehensive parameter 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?
Schema description coverage is 100%, so the schema fully documents all 9 parameters. The description adds no parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info 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 action ('Create a new pull request') and resource ('pull request'), with the parenthetical clarifying GitLab terminology. It distinguishes from siblings like 'merge_pull_request' (which merges rather than creates) and 'create_issue' (different resource). However, it doesn't explicitly differentiate from all siblings like 'create_branch' or 'create_comment'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing existing branches), when to use 'create_issue' instead for non-code changes, or how it relates to 'merge_pull_request' for completing the workflow. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get details' which implies a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what specific details are returned (e.g., title, status, assignee). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain what 'details' include, potential errors, or integration with siblings like 'list_comments', leaving the agent with insufficient context for 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%, with clear descriptions for both parameters ('repo' and 'issue_number'). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, so it meets the baseline 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 'Get' and resource 'details of a specific issue in a project', making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_issues' (which lists multiple issues) or 'get_pull_request' (which retrieves a different resource type), missing full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer this over 'list_issues' for single-issue retrieval, or clarify that it's for detailed metadata rather than comments or updates, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions retrieving log/trace output but fails to detail critical aspects such as authentication requirements, rate limits, output format (e.g., text, JSON), or whether it includes real-time streaming. This leaves significant gaps for agent understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that efficiently conveys the core function without unnecessary words. It is front-loaded with the essential action and resource, making it highly concise and well-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 tool's complexity (retrieving job logs, which may involve permissions and data formats), lack of annotations, and absence of an output schema, the description is insufficient. It does not address behavioral traits, return values, or error handling, leaving the agent with incomplete information for reliable 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?
The input schema has 100% description coverage, clearly documenting both parameters ('repo' and 'job_id') with details on formats and constraints. The description does not add any meaningful semantic context beyond what the schema provides, such as examples or edge cases, so it meets the baseline 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 action ('Get') and target resource ('log/trace output of a CI/CD job'), making the purpose evident. However, it does not distinguish this tool from potential siblings like 'list_pipeline_jobs' or 'get_pipeline', which might also relate to job data, missing explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. For example, it does not specify if this is for detailed debugging versus summary views or how it relates to tools like 'get_pipeline' or 'list_pipeline_jobs', leaving usage context 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves details but doesn't specify what those details include (e.g., status, duration, artifacts), whether it's a read-only operation, error handling for invalid IDs, or any rate limits. For a tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get details of a specific CI/CD pipeline') and adds clarifying context ('workflow run in GitHub'). There is no wasted verbiage, and it's appropriately sized for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a retrieval tool with no output schema and no annotations), the description is incomplete. It doesn't explain what 'details' are returned, error conditions, or how it integrates with siblings like 'list_pipeline_jobs'. For a tool without structured output, more context on return values is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for both parameters ('repo' and 'pipeline_id'). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate since the schema fully documents the parameters, but the description doesn't enhance 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 action ('Get details') and resource ('specific CI/CD pipeline'), with parenthetical clarification that this refers to 'workflow run in GitHub'. It distinguishes from siblings like 'list_pipelines' by focusing on a single pipeline, though it doesn't explicitly name that sibling. The purpose is specific but could be slightly more precise about what 'details' include.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 is provided. The description implies usage for a specific pipeline ID, but it doesn't mention when to choose this over 'list_pipelines' or 'list_pipeline_jobs', nor does it discuss prerequisites like authentication or repository access. Usage is inferred from the name and parameters 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 full burden. It states the tool retrieves diffs to see modified files, but doesn't disclose behavioral traits like whether it's read-only (implied by 'Get'), rate limits, authentication needs, output format (e.g., patch vs. summary), or pagination. For a tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is front-loaded and efficient, with no wasted words. It directly states the purpose, though it could be slightly more structured (e.g., separating intent from outcome).
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. It doesn't explain what the diffs look like (e.g., raw patch, file list), behavioral constraints, or error handling. For a tool that likely returns complex data, 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?
Schema description coverage is 100%, with clear parameter documentation in the schema. The description adds no parameter-specific information beyond what the schema provides (e.g., no examples or edge cases). Baseline 3 is appropriate as the schema handles semantics effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'changes/diffs of a pull request', specifying the action and target. It distinguishes from siblings like 'get_pull_request' (which likely returns metadata) by focusing on file modifications, but doesn't explicitly name alternatives or contrast scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'get_pull_request' or 'list_commits'. The description implies usage for viewing file modifications in a PR, but lacks explicit when/when-not instructions or prerequisite context (e.g., after identifying a PR number).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the 'recursive' parameter's effect but fails to describe key behaviors such as pagination handling (implied by 'page' and 'per_page' parameters), rate limits, authentication needs, error conditions, or the format of returned data. For a tool with 6 parameters and no annotations, this is a significant gap, warranting a score of 2.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the core purpose in the first sentence and adding a useful tip in the second. Both sentences earn their place by providing essential information without waste. However, it could be slightly more structured by explicitly mentioning pagination or other key behaviors, preventing a perfect score of 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits like pagination, error handling, and return format, which are crucial for effective use. Without annotations or an output schema, the description should compensate more by explaining these aspects, but it doesn't, resulting in a score of 2.
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%, meaning all parameters are documented in the input schema. The description adds minimal value by explaining the 'recursive' parameter's effect ('to get full tree'), but doesn't provide additional semantics beyond what the schema already covers. According to the rules, with high schema coverage (>80%), the baseline score is 3, and the description doesn't significantly enhance parameter understanding, so it remains at 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 clearly states the tool's purpose: 'List files and directories in a repository.' It specifies the verb ('List') and resource ('files and directories in a repository'), which is specific and actionable. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_branches' or 'list_commits', which reduces the score from a 5 to a 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 usage guidance with 'Use recursive=true to get full tree,' which hints at a parameter-specific behavior but doesn't offer broader context. It lacks explicit guidance on when to use this tool versus alternatives like 'get_file_contents' for file details or 'search_code' for searching, and doesn't mention prerequisites or exclusions. This results in a score of 2, as there's no substantial guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the basic action but lacks crucial behavioral details: it doesn't mention pagination behavior (implied by 'page' and 'per_page' parameters but not explained), rate limits, authentication requirements, or what the output format looks like. For a list operation with 6 parameters, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that states the core functionality without unnecessary words. It's front-loaded and efficiently communicates the essential purpose, earning its place fully.
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 (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain the return values, pagination behavior, or any constraints like rate limits. For a list operation that likely returns structured data, more context is needed to help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 in the schema. The description adds no additional parameter information beyond implying the tool works on 'issue or pull request' (which aligns with the 'type' parameter). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('comments on an issue or pull request'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_issue' or 'get_pull_request', which might also return comment data, but the focus on listing comments specifically is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't mention whether 'get_issue' or 'get_pull_request' might include comments, or if this is the primary way to retrieve comment data. There's no context about prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral information. It mentions filtering capabilities but doesn't disclose pagination behavior (implied by parameters), rate limits, authentication requirements, whether it's read-only, or what the output format looks like. For a 9-parameter tool with no 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 perfectly concise - one sentence that states the core purpose and enumerates filtering options. Every word earns its place with zero redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter tool with no annotations and no output schema, the description is inadequate. It doesn't explain the return format, pagination behavior, authentication requirements, or error conditions. While the schema covers parameter documentation well, the overall context for proper tool invocation is incomplete.
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 thoroughly. The description adds marginal value by listing the filterable dimensions (branch, path, date range, author) which maps to some parameters, but doesn't provide additional context beyond what's in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and resource 'commits in a repository', making the purpose immediately understandable. It distinguishes from siblings like list_branches or list_issues by specifying commits, but doesn't explicitly differentiate from other commit-related tools (none exist in the sibling list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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, compare with search_code for commit searching, or indicate when filtering is appropriate versus using other list tools. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'optional filters' but lacks critical behavioral details such as pagination behavior (implied by 'page' and 'per_page' parameters), rate limits, authentication needs, or what the output looks like (e.g., list format). This is inadequate for a tool with 10 parameters and no output 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?
The description is a single, efficient sentence that front-loads the core purpose ('List issues in a project') and adds a key detail ('with optional filters'). There is no wasted verbiage, making it appropriately concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (10 parameters, no output schema, and no annotations), the description is insufficient. It doesn't address behavioral aspects like pagination, error handling, or output format, leaving significant gaps for an AI agent to understand how to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing detailed descriptions for all parameters. The description adds minimal value beyond the schema by mentioning 'optional filters', but doesn't explain parameter interactions or provide additional context. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('issues in a project'), making the purpose specific and understandable. However, it doesn't distinguish this tool from sibling tools like 'get_issue' or 'list_pull_requests', which would require explicit differentiation for 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 'get_issue' (for single issues) or 'search_code' (for code-related queries). It mentions 'optional filters' but doesn't specify contexts or exclusions, leaving usage unclear relative to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'to see results' but doesn't disclose key behaviors: it's a read-only list operation (implied by 'List'), requires authentication, likely has pagination (hinted by page/per_page params but not explained), or rate limits. The description adds minimal behavioral context beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action. It could be slightly more structured by explicitly mentioning filtering or pagination, but it avoids waste and is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with 5 parameters, 100% schema coverage, and no output schema, the description is minimally adequate. It states the purpose but lacks context on usage, behavioral details, or output format. Given the schema handles parameters well, the description meets a basic threshold but leaves gaps in guidance and transparency.
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 full parameter documentation. The description adds no parameter-specific information beyond what's in the schema (e.g., doesn't clarify repo format differences or default behaviors). Baseline 3 is appropriate as 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 ('List') and resource ('all jobs in a CI/CD pipeline'), making the purpose understandable. It distinguishes from siblings like 'list_pipelines' by focusing on jobs within a pipeline, but doesn't explicitly contrast with 'get_job_log' which retrieves logs for a specific job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 like needing a pipeline ID first (available via 'list_pipelines'), nor does it differentiate from 'get_job_log' for detailed job information. The description only states the basic function without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions 'optional filters', it doesn't describe key behaviors: whether this is a read-only operation, how pagination works (beyond schema parameters), rate limits, authentication requirements, error conditions, or the format/structure of returned data. For a list operation with 10 parameters, this leaves significant gaps in understanding tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 ('List pull requests') and adds necessary context ('merge requests in GitLab') and scope ('with optional filters'). Every word earns its place with zero redundancy or wasted space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain what the tool returns (e.g., list of PR objects with fields), how results are structured, pagination behavior beyond schema parameters, or error handling. For a list operation that likely returns complex data, more context is needed to use it 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 10 parameters thoroughly with descriptions, enums, and constraints. The description adds minimal value beyond stating 'with optional filters', which is already implied by the parameter names in the schema. This meets the baseline for high schema coverage where the description doesn't need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'List pull requests (merge requests in GitLab) with optional filters', which includes a specific verb ('List') and resource ('pull requests'), plus scope clarification for GitLab terminology. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_pull_request' (singular) or 'list_issues', which might have overlapping functionality 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 sibling tools like 'get_pull_request' (for single PR details) or 'list_issues' (for related functionality), nor does it specify prerequisites, appropriate contexts, or exclusions. The agent must infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose that this is a destructive/mutative operation, potential permission requirements, side effects (e.g., branch deletion if 'delete_branch' is true), or error conditions (e.g., merge conflicts). The description is minimal and misses critical context 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 with zero waste. It's front-loaded with the core purpose and includes a brief clarification for GitLab users, making it appropriately sized and structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It lacks behavioral transparency, usage guidelines, and details on return values or errors. Given the complexity and mutation nature, more context is needed to ensure safe and correct 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 fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema, such as explaining interactions between parameters (e.g., 'squash' and 'commit_message'). Baseline 3 is appropriate as the schema handles 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 ('merge') and target resource ('pull request'), with a helpful parenthetical clarifying GitLab terminology. It distinguishes from siblings like 'create_pull_request' or 'get_pull_request' by focusing on the merge operation, though it doesn't explicitly contrast with all potential alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., pull request must be mergeable), exclusions (e.g., conflicts), or related tools like 'create_pull_request' for creation or 'get_pull_request' for checking status.
Agents often have multiple tools that could apply. Explicit usage guidance like "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. 'Update' implies mutation, but the description lacks details on permissions required, whether changes are reversible, side effects (e.g., notifications), or error handling. It doesn't mention that 'labels' replaces existing ones (hinted in schema) or rate limits. This is a significant gap 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 directly states the tool's purpose without fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (mutation with 7 parameters) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, side effects, or error handling, nor does it explain return values. For a mutation tool with no structured safety hints, this leaves critical 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%, so the schema already documents all 7 parameters thoroughly (e.g., 'repo' identifier formats, 'labels' replaces existing). The description adds no additional meaning beyond the schema, such as explaining interactions between parameters or default behaviors. 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 ('Update') and resource ('an existing issue in a project'), making the purpose unambiguous. It distinguishes from sibling tools like 'create_issue' (for creation) and 'get_issue' (for retrieval). However, it doesn't specify what aspects can be updated, 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., needing an existing issue), exclusions (e.g., not for creating issues), or comparisons with siblings like 'create_issue' or 'get_issue'. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks critical details: it doesn't specify what information is returned (e.g., username, email, permissions), whether it requires authentication (implied but not explicit), or any limitations (e.g., rate limits or error conditions). For a tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without any fluff. It's front-loaded with the essential information ('Get information about the currently authenticated user'), and every word earns its place. This is an excellent example of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what information is returned, which is crucial for an agent to understand the tool's utility. While the purpose is clear, the behavioral and output details are missing, making it inadequate for full contextual understanding.
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 the input schema has 100% description coverage (though empty). The description appropriately doesn't discuss parameters, which is correct for a parameterless tool. No additional parameter semantics are needed, so it meets the baseline for this case.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get information') and the target resource ('the currently authenticated user'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings like 'get_issue' or 'get_pull_request', but the specificity of 'authenticated user' provides inherent differentiation from other 'get_' tools that target repository objects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps 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 (like authentication status), use cases (e.g., checking permissions or user identity), or contrast with other user-related operations that might exist in the broader system. The agent must infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the return format ('matching files and lines') but lacks critical details: whether this is a read-only operation (implied but not stated), pagination behavior (though parameters suggest it), rate limits, authentication requirements, or error conditions. For a search tool with 5 parameters, 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 perfectly concise: two sentences that directly state the tool's function and return value with zero wasted words. It's front-loaded with the core purpose and follows with essential output information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with full schema coverage but no annotations and no output schema, the description is minimally adequate. It covers the basic purpose and return format but lacks behavioral context (transparency issues) and usage guidance. For a search tool with pagination and repository targeting, more context about limitations, authentication, or error handling would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema (e.g., doesn't explain query syntax, ref defaults, or pagination behavior). Baseline 3 is appropriate when the schema does all the work, though the description could have added value by clarifying search semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search for code in a repository' specifies the verb (search) and resource (code in repository). It distinguishes from siblings like get_file_contents (retrieve specific file) or list_commits (list commits), but doesn't explicitly differentiate from other search-like tools (none exist in sibling list). The second sentence adds value by specifying the return format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., repository access), when not to use it (e.g., for metadata searches), or how it compares to similar operations like get_repository_tree (which lists files without content search). The agent must infer usage from the name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but lacks critical details: whether it requires authentication, rate limits, what happens with non-existent paths, if it returns raw content or metadata, or if there are size limitations. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, achieving ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (fetching file/directory contents), lack of annotations, and no output schema, the description is insufficiently complete. It doesn't explain return values, error handling, authentication needs, or differences between file vs. directory responses. For a tool with 3 parameters and no structured safety hints, more contextual detail 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?
Schema description coverage is 100%, so the schema fully documents all three parameters (repo, path, ref) with clear descriptions. The description adds no additional parameter semantics beyond what's already in the schema, such as examples or edge cases. This meets the baseline for high schema coverage but doesn't enhance 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 'Get' and the resource 'contents of a file or directory from a repository', making the purpose immediately understandable. It distinguishes itself from siblings like get_repository_tree (which lists files) and search_code (which searches content). However, it doesn't specify the exact format of the returned contents (e.g., raw text, metadata), 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving file/directory contents, but provides no explicit guidance on when to use this tool versus alternatives like get_repository_tree (for listing) or search_code (for searching). There's no mention of prerequisites, error conditions, or specific scenarios where this tool is preferred, leaving usage context somewhat 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions optional search functionality but fails to describe critical behaviors like pagination (implied by 'page' and 'per_page' parameters but not explained), rate limits, authentication requirements, or error handling. For a tool with pagination parameters, this lack of behavioral context 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 extremely concise with only two sentences, front-loading the core purpose and efficiently adding the optional search feature. Every word earns its place, and there is no redundancy or unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters including pagination), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return format (e.g., list structure, branch details), pagination behavior, or error cases. For a tool that likely returns structured data, this omission leaves the agent without crucial context for proper invocation and response handling.
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 input schema. The description adds minimal value beyond the schema by hinting at the optional 'search' functionality but doesn't provide additional context like search syntax or examples. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly 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 with a specific verb ('List') and resource ('branches in a repository'), making it immediately understandable. It distinguishes itself from siblings like 'create_branch' by focusing on retrieval rather than creation. However, it doesn't explicitly differentiate from other list tools like 'list_issues' or 'list_pull_requests' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the phrase 'Optionally search for specific branches,' suggesting this tool is for listing branches with optional filtering. However, it provides no explicit guidance on when to use this versus alternatives like 'search_code' or how it relates to other list operations. No exclusion criteria or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'optional filters' but doesn't disclose key behavioral traits: it doesn't specify that this is a read-only operation (though implied by 'List'), doesn't mention pagination behavior (though parameters exist), doesn't describe rate limits, authentication needs, or what the output looks like. The description adds minimal value beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place, with no redundancy. However, it could be slightly more structured by explicitly separating the core action from the filtering capability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with 7 parameters, 100% schema coverage, and no output schema, the description is minimally adequate. It states what the tool does but lacks context about output format, pagination behavior, error conditions, or how it integrates with sibling tools. Without annotations, more behavioral disclosure would be helpful for an agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 7 parameters. The description adds no specific parameter information beyond mentioning 'optional filters' generically. It doesn't explain parameter relationships, default behaviors, or usage examples. Baseline 3 is appropriate when 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 ('List') and resource ('CI/CD pipelines'), with additional clarification that these are 'workflow runs in GitHub'. It distinguishes from siblings like 'get_pipeline' (singular) and 'list_pipeline_jobs' (jobs within pipelines). However, it doesn't explicitly mention how it differs from other list tools like 'list_issues' or 'list_commits' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'with optional filters', suggesting this tool is for retrieving pipelines with filtering capabilities. It doesn't provide explicit guidance on when to use this versus alternatives like 'get_pipeline' (for a single pipeline) or 'list_pipeline_jobs' (for jobs within a pipeline), nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it 'gets details' without specifying what details are returned, authentication requirements, rate limits, or error conditions. It mentions GitLab terminology but doesn't clarify platform-specific behaviors or response formats.
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 purpose and includes only essential clarification about GitLab terminology, making it appropriately sized for its function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read operation with 2 parameters and 100% schema coverage, the description is minimally adequate but lacks output details (no output schema) and behavioral context. It covers the basic purpose but doesn't address what 'details' include or platform nuances, leaving gaps for agent 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 both parameters. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for adequate coverage through structured data alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get details' and resource 'pull request', with parenthetical clarification for GitLab terminology. It distinguishes from siblings like list_pull_requests (listing vs getting details) and get_pull_request_diffs (details vs diffs), though not explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the description's focus on retrieving details for a specific pull request, suggesting it should be used when you have the PR number rather than for listing. However, no explicit guidance on when to use this vs alternatives like get_pull_request_diffs is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool performs write operations ('push') with multiple file actions, but lacks critical details: required permissions, whether changes are reversible, rate limits, error handling, or what happens on conflicts. For a mutation tool with 7 parameters and no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It front-loads the core purpose ('Push multiple files to a repository in a single commit') and adds only essential elaboration ('Supports create, update, delete, and move actions'). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, mutation operations, no output schema, and no annotations), the description is adequate but incomplete. It covers the basic purpose and action types, but lacks behavioral context like permissions, side effects, or return values. For a batch file mutation tool, more guidance on usage and outcomes would be beneficial.
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 7 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'multiple files' and 'single commit', which aligns with the 'actions' array parameter, but doesn't provide additional syntax, format, or constraint details. Baseline 3 is appropriate when schema does the heavy lifting.
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 specific action ('push multiple files'), target resource ('to a repository'), and scope ('in a single commit'), with explicit enumeration of supported operations ('create, update, delete, and move actions'). This distinguishes it from sibling tools like create_branch or update_issue which handle different repository operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'push multiple files' and 'single commit', suggesting batch file operations rather than individual file changes. However, it provides no explicit guidance on when to use this tool versus alternatives like create_branch for branch operations or update_issue for issue tracking, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool creates a branch, it doesn't disclose important behavioral traits like whether this requires specific permissions, what happens if the branch already exists, whether the operation is atomic, or what kind of response/error messages to expect. For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that each earn their place. The first states the core purpose, the second provides usage guidance. There's zero wasted text, and the information is front-loaded with the most important statement first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description provides adequate purpose and usage guidance but lacks important behavioral context. It doesn't explain what happens on success/failure, what permissions are needed, or what the tool returns. Given the complexity of a branch creation operation in version control systems, more context would be helpful.
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 fully documents all three parameters (repo, name, ref). The description doesn't add any parameter-specific information beyond what's in the schema, such as naming conventions, ref format examples, or validation rules. Baseline 3 is appropriate when the schema does all the parameter documentation work.
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 specific action ('Create a new branch') and resource ('in the repository'), distinguishing it from sibling tools like list_branches or push_files. It provides a complete verb+resource+context statement that leaves no ambiguity about what this tool does.
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 ('before making code changes to work on a separate branch'), providing clear context for its application. It distinguishes this from other branching-related operations by emphasizing it's for creating a new branch specifically for development work.
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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