GitLab MCP Server

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific GitLab resources and actions. For example, merge request operations (approve, create, get, update, merge), pipeline operations (create, cancel, retry), and branch/commit operations are all well-separated with no overlapping functionality.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case throughout (e.g., create_merge_request, list_pipelines, get_branch). The naming convention is perfectly uniform across all 30 tools, making them easily predictable and readable.
Tool Count3/5
With 30 tools, this is borderline heavy for an MCP server. While GitLab has extensive functionality, the tool count approaches the upper limit of what's typically manageable, potentially overwhelming agents despite good organization.
Completeness5/5
The tool surface provides comprehensive coverage of GitLab's core functionality including projects, branches, commits, merge requests, pipelines, and jobs. It offers complete CRUD/lifecycle operations for all major resources with no obvious gaps for agent workflows.
Average 2.9/5 across 30 of 30 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the action ('取消 Pipeline') without explaining what cancellation does (e.g., stops execution, sets status to canceled), permissions required, side effects, or response behavior. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with a clear header and parameter list, but it's under-specified rather than concise. The first line '取消 Pipeline' is redundant, and the parameter explanations are minimal. While structured, it lacks essential information that would justify its brevity for a mutation 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 tool's complexity (a mutation with 2 parameters), no annotations, 0% schema coverage, but with an output schema, the description is incomplete. It doesn't cover behavioral aspects like effects, permissions, or error conditions. The output schema may help with return values, but the description fails to provide necessary context for safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters ('project_id: 專案 ID 或路徑', 'pipeline_id: Pipeline ID') but adds minimal meaning beyond the schema's titles ('Project Id', 'Pipeline Id'). The Chinese note for project_id ('專案 ID 或路徑') hints it can be an ID or path, but this is already implied by the schema's anyOf type. It doesn't explain format, constraints, or relationships between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states '取消 Pipeline' (Cancel Pipeline), which is a tautology that merely restates the tool name in Chinese. While it indicates the action and resource, it lacks specificity about what cancellation entails (e.g., stopping execution, marking as failed) and doesn't distinguish it from sibling tools like 'retry_pipeline' or 'get_pipeline'. This provides minimal clarity beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., pipeline must be running), exclusions (e.g., cannot cancel completed pipelines), or comparisons to siblings like 'retry_pipeline' or 'create_pipeline'. This leaves the agent with no 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states it retrieves job details without mentioning whether this is a read-only operation, what permissions are required, whether it returns real-time or cached data, or how it handles errors. For a tool with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with a clear purpose statement followed by parameter documentation. The bilingual format (Chinese purpose, English parameter labels) is slightly inconsistent but doesn't significantly impact readability. The structure is front-loaded with the main purpose 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?
Given that an output schema exists, the description doesn't need to explain return values. However, for a tool with 2 required parameters, 0% schema description coverage, and no annotations, the description provides only basic purpose and parameter listing without addressing usage context, behavioral characteristics, or parameter details. It's minimally adequate but leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds minimal parameter semantics by listing 'project_id: 專案 ID 或路徑' and 'job_id: Job ID' but doesn't explain format expectations, where to find these IDs, or what constitutes valid values. This doesn't adequately compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states '取得 Job 詳細資訊' (Get job details) which provides a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_job_log' or 'get_pipeline' that also retrieve job-related information. The purpose is understandable but lacks specificity about what kind of job details are retrieved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. With siblings like 'get_job_log' (for logs), 'get_pipeline' (for pipeline context), and 'retry_job' (for job control), the description offers no indication of when this specific job details retrieval tool is appropriate versus other job-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states this retrieves information without mentioning authentication requirements, rate limits, error conditions, or what '詳細資訊' (detailed information) specifically includes. For a read operation with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief with a clear purpose statement followed by parameter documentation. However, the parameter section uses minimal labels rather than full explanations, and the overall structure could be more front-loaded with critical information about when to use this tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), 2 parameters with 0% schema coverage, and no annotations, the description is minimally complete but has significant gaps. It states the basic purpose but lacks usage guidance, parameter semantics, and behavioral context that would be needed for optimal agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate but provides minimal parameter context. It lists the two parameters with brief labels ('專案 ID 或路徑' - project ID or path, 'Pipeline ID') but doesn't explain format expectations, relationship between parameters, or what constitutes valid values. This doesn't adequately compensate for the schema coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states '取得 Pipeline 詳細資訊' (Get pipeline detailed information), which provides a clear verb ('取得' - get) and resource ('Pipeline'). However, it doesn't distinguish this from sibling tools like 'list_pipelines' or 'get_project', making it somewhat vague about its specific scope beyond being a retrieval operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention sibling tools like 'list_pipelines' (for listing multiple pipelines) or 'get_project' (for project-level information), nor does it specify prerequisites or appropriate contexts for retrieving detailed pipeline 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?
No annotations are provided, so the description carries the full burden. It mentions listing jobs but doesn't disclose behavioral traits like whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior (implied by page/per_page but not explained), or what happens with invalid inputs. This leaves significant gaps for an agent to understand how to use it safely and effectively.
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 appropriately sized and front-loaded, starting with the main purpose followed by parameter listings. However, the structure includes a redundant 'Args:' section that repeats parameter names without adding much value, slightly reducing efficiency. Overall, it's concise but could be more streamlined.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters with 0% schema coverage and an output schema exists (which handles return values), the description is partially complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines. With no annotations, it should do more to explain how the tool behaves, but the output schema mitigates some gaps by defining return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters (project_id, pipeline_id, page, per_page) but adds minimal semantics: '專案 ID 或路徑' clarifies project_id can be an ID or path, which is helpful, but doesn't explain pipeline_id beyond 'Pipeline ID' or the pagination parameters. This partially addresses the coverage gap but leaves key details unclear, such as format expectations or default behaviors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states '列出 Pipeline 的所有 Jobs' (List all jobs of a pipeline), which provides a clear verb ('list') and resource ('jobs of a pipeline'). However, it doesn't distinguish this tool from siblings like 'get_job' (which retrieves a single job) or 'list_pipelines' (which lists pipelines rather than jobs), leaving the purpose somewhat vague in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention using 'get_job' for details on a specific job or 'list_pipelines' to find pipelines first. The description only states what it does, with no context for selection among related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action ('重試 Pipeline') but doesn't disclose behavioral traits such as what 'retry' entails (e.g., re-running failed jobs, permissions required, side effects, or response format). This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the tool's purpose, followed by parameter names. It avoids unnecessary fluff, but the parameter section is minimal and could be more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a mutation tool with no annotations, 0% schema coverage, and an output schema (which reduces need to describe returns), the description is incomplete. It states the action but lacks details on behavior, parameters, and usage context, making it minimally viable but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters ('project_id' and 'pipeline_id') but adds no meaning beyond their names—no explanation of what they represent, valid formats (e.g., integer vs. string for project_id), or where to find them. This fails to address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool '重試 Pipeline' (retry pipeline), which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'retry_job' or 'cancel_pipeline', leaving ambiguity about when to use each. The purpose is understandable but lacks 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?
No guidance is provided on when to use this tool versus alternatives like 'retry_job', 'cancel_pipeline', or 'create_pipeline'. The description only lists parameters without context about prerequisites, timing, or relationships to other pipeline operations.
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 detailed information, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'detailed information' entails. This leaves significant gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the purpose, followed by parameter listings. However, the parameter section is brief and could be more integrated, but overall it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description doesn't need to explain return values. However, with no annotations, low schema coverage, and multiple sibling tools, the description lacks completeness in guiding usage, behavioral context, and parameter details, making it only minimally 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 description coverage is 0%, so the description must compensate. It lists the parameters (project_id, branch_name) and provides minimal semantics (e.g., '專案 ID 或路徑' for project_id), but doesn't explain formats, constraints, or examples. This adds some value over the bare schema but is insufficient for full understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the purpose ('取得分支詳細資訊' translates to 'Get branch detailed information'), which is clear but basic. It doesn't distinguish this tool from siblings like 'list_branches' or 'compare_branches', leaving ambiguity about scope and differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this is for retrieving metadata of a single branch versus listing multiple branches (list_branches) or comparing branches (compare_branches), which are relevant sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions pagination parameters (page, per_page) which hints at paginated results, but doesn't disclose other behavioral traits like authentication requirements, rate limits, error conditions, or what happens when parameters are invalid. The description is minimal beyond parameter listing.
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 appropriately sized with a clear header and parameter list. It's front-loaded with the purpose, though the parameter explanations are brief. No redundant sentences, but could be more structured with usage examples or constraints.
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 0% schema coverage and no annotations, the description is incomplete—it lacks behavioral details, error handling, and usage context. However, an output schema exists (not shown here), which may cover return values, reducing the burden on the description. The description provides basic parameter semantics but misses broader context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides brief Chinese explanations for each parameter (e.g., '專案 ID 或路徑' for project_id, '分支或標籤名稱' for ref_name), adding some semantic context beyond the schema's titles. However, it doesn't explain parameter interactions, constraints, or provide examples, leaving significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states '列出 Commits' (List Commits) which clearly indicates the verb and resource, but it's vague about scope and doesn't differentiate from sibling tools like 'get_commit' or 'list_repository_tree'. It doesn't specify whether this lists all commits in a repository or commits for specific criteria.
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_commit' (for single commit details) or 'list_repository_tree' (for file listings). The description only lists parameters without context about appropriate use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions pagination via 'page' and 'per_page' parameters, implying a list operation, but does not disclose behavioral traits like rate limits, authentication needs, error handling, or what the output contains (though an output schema exists). This leaves gaps for a tool with no annotations.
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 structured with a brief purpose statement followed by parameter explanations. It avoids unnecessary details, though it could be more front-loaded with key usage information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (list operation with pagination), no annotations, and an output schema (which reduces need to explain returns), the description is partially complete. It covers basic purpose and parameters but lacks behavioral context and usage guidelines, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics: it notes that 'project_id' can be an ID or path and that 'page' and 'per_page' are for pagination. However, with 0% schema description coverage and 3 parameters, this is insufficient to fully compensate. The baseline is lowered due to low coverage, but some value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool '列出專案成員' (list project members), which clearly indicates its purpose. However, it does not differentiate from sibling tools like 'list_projects' or 'list_branches' beyond the resource type, and the title is null, making it somewhat vague in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as filtering members or handling specific project types. It lists parameters but does not explain usage context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool lists notes but doesn't disclose behavioral traits like whether it's read-only (implied by 'list'), authentication needs, rate limits, error conditions, or pagination details (beyond parameter names). The description adds minimal context 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 appropriately sized with a clear main sentence followed by a structured Args section. There's no wasted text, and information is front-loaded with the core purpose stated first. The bilingual presentation (Chinese description with some English terms) is efficient but doesn't hinder clarity.
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 moderate complexity (4 parameters, 2 required), no annotations, and the presence of an output schema (which handles return values), the description is minimally adequate. It covers the basic purpose but lacks usage guidelines, detailed parameter semantics, and behavioral context. The output schema relieves some burden, but gaps remain for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameter names in the Args section but provides no semantic meaning beyond what's in the schema (e.g., 'project_id: 專案 ID 或路徑' translates to 'project ID or path', which is already clear from the schema title). It doesn't explain format expectations, constraints, or interactions between parameters like pagination behavior.
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 ('列出' meaning 'list') and resource ('Merge Request 的留言' meaning 'Merge Request notes'), providing a specific verb+resource combination. It distinguishes this tool from siblings like 'create_merge_request_note' (which creates notes) and 'get_merge_request' (which retrieves MR metadata). However, it doesn't explicitly mention pagination behavior, which is a minor gap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention related tools like 'get_merge_request' (which might include some notes) or 'create_merge_request_note' (for adding notes), nor does it specify prerequisites or contextual constraints. 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?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'approve' implies a write operation, the description doesn't clarify what 'approve' actually does (e.g., adds approval, changes status), whether it's reversible, what permissions are required, or what happens on success/failure.
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 appropriately brief with a clear title-like statement followed by parameter explanations. The bilingual presentation (Chinese title, English parameter names) is slightly unconventional but doesn't significantly impact clarity.
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 but with an output schema, the description provides minimal but functional coverage. It identifies the tool's purpose and parameters but lacks behavioral context, usage guidance, and doesn't leverage the output schema's existence to explain what the tool returns.
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 0%, so the schema provides no parameter documentation. The description adds basic semantic meaning for both parameters ('project ID or path' and 'MR IID'), establishing what they represent. However, it doesn't provide format details, constraints, or examples.
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 ('approve') and resource ('Merge Request'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar tools like 'merge_merge_request' or 'update_merge_request' that might also affect merge request status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like 'merge_merge_request' or 'update_merge_request'. The description doesn't mention prerequisites (e.g., whether the user needs specific permissions) or contextual constraints.
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 tool compares differences but doesn't disclose behavioral traits like what format the output takes (e.g., diff format, summary statistics), whether it's read-only (implied but not explicit), rate limits, or authentication needs. For a comparison 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?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. The parameter list is structured but could be more integrated. There's no wasted text, though it lacks depth in usage or behavior.
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 moderate complexity (3 parameters, no annotations, but has an output schema), the description is minimally adequate. The output schema likely covers return values, reducing the need for output details in the description. However, it misses key context like comparison scope (e.g., file-level, commit-level) and behavioral traits, leaving gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics by listing parameters with brief labels ('專案 ID 或路徑', '起始分支/commit', '目標分支/commit'), but doesn't explain formats, constraints, or examples. It partially compensates for the schema gap but leaves key details unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as '比較兩個分支或 commit 的差異' (compare differences between two branches or commits), which is a specific verb+resource combination. It distinguishes itself from siblings like 'get_branch' or 'list_branches' by focusing on comparison rather than retrieval. However, it doesn't explicitly differentiate from 'get_merge_request_changes' which might also involve comparisons.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., for code review or deployment checks), or exclusions. Given siblings like 'get_merge_request_changes' that might overlap, this lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool creates a note, implying a write operation, but doesn't disclose behavioral traits such as required permissions, rate limits, whether the note is editable/deletable, or how it interacts with the MR workflow. The description adds minimal context 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 appropriately sized and front-loaded, with the main purpose stated first followed by parameter details in a structured format. Every sentence earns its place, though the parameter explanations could be slightly more detailed without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a write operation with 3 parameters), lack of annotations, and presence of an output schema, the description is moderately complete. It covers the basic action and parameters but lacks behavioral context and usage guidelines. The output schema likely handles return values, so the description doesn't need to explain those.
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 0%, so the description must compensate. It provides brief explanations for each parameter (e.g., '專案 ID 或路徑' for project_id, '留言內容（支援 Markdown）' for body), adding meaning beyond the bare schema. However, it doesn't fully detail constraints, formats, or examples, leaving gaps in 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 ('新增' meaning 'add/create') and resource ('Merge Request 留言' meaning 'Merge Request note/comment'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_merge_request_notes' or 'update_merge_request', which would require a more precise distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an existing merge request), exclusions, or comparisons to sibling tools like 'list_merge_request_notes' for reading notes or 'update_merge_request' for modifying MR details.
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 triggers a pipeline but doesn't disclose behavioral traits: whether it's idempotent, what permissions are needed, if it's asynchronous, rate limits, error conditions, or what happens on success (e.g., returns pipeline ID). 'Trigger' implies a write/mutation, but details are missing 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the main purpose, followed by parameter details in a structured 'Args:' section. The description is appropriately sized with no redundant sentences. However, the parameter explanations could be more integrated rather than listed, and the JSON example is slightly verbose but informative.
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 no annotations, 3 parameters with 0% schema coverage, and an output schema exists (so return values needn't be explained), the description is moderately complete. It covers the basic action and parameters but lacks behavioral context (e.g., mutation effects, error handling) and usage guidelines, which are important for a pipeline creation tool with write implications.
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 0%, so the description must compensate. It adds meaning for all three parameters: 'project_id' as project ID or path, 'ref' as branch name or tag, and 'variables' as pipeline variables with JSON format example. However, it doesn't explain parameter interactions, constraints (e.g., ref must exist), or optionality (variables is optional per schema default). Partial compensation given the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('觸發新的 CI/CD Pipeline' - trigger new CI/CD pipeline) and identifies the resource (pipeline). It distinguishes from siblings like 'get_pipeline', 'list_pipelines', 'cancel_pipeline', and 'retry_pipeline' by specifying creation/triggering rather than retrieval or modification. However, it doesn't explicitly contrast with 'retry_pipeline' which also initiates pipeline execution.
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. The description doesn't mention prerequisites (e.g., project access, branch existence), when not to use it (e.g., for existing pipelines), or direct alternatives among siblings like 'retry_pipeline' for restarting existing pipelines. 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 only states what the tool does ('取得 Commit 詳細資訊') without disclosing behavioral traits like whether it's read-only, what authentication is needed, rate limits, error conditions, or what format/details the commit information includes. For a tool with no 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?
The description is appropriately sized and front-loaded: the main purpose is stated first, followed by parameter clarifications. There's no wasted text. However, the structure could be slightly improved by separating the purpose from parameter explanations more clearly.
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 that there's an output schema (which handles return values), no annotations, and low schema coverage (0%), the description is minimally complete. It states the purpose and clarifies parameters briefly, but lacks behavioral context and usage guidance. For a simple read operation with output schema, it's adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds minimal semantics: it clarifies that 'project_id' can be an ID or path, and 'sha' can be full or shortened. However, it doesn't explain what a 'project_id' or 'sha' represents in context, or provide examples. With 0% schema coverage, the description partially compensates but not fully.
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 purpose: '取得 Commit 詳細資訊' (Get commit details/information). It specifies the verb ('取得' - get/retrieve) and resource ('Commit 詳細資訊' - commit details). However, it doesn't explicitly differentiate from sibling tools like 'list_commits' or 'get_merge_request_commits', which reduces it from 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 sibling tools like 'list_commits' (for listing multiple commits) or 'get_merge_request_commits' (for commits within a merge request). 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 it retrieves detailed information but doesn't disclose behavioral traits like whether it's read-only (implied but not stated), authentication requirements, rate limits, error conditions, or what 'detailed information' includes. The description is minimal and lacks necessary 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but not optimally structured. It starts with the purpose statement, then has an 'Args:' section that somewhat duplicates the schema. The two-sentence format is concise, but the 'Args' section adds minimal value beyond the schema and could be integrated more naturally. It's front-loaded with the main purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and simple parameters, the description is moderately complete. It states the purpose and parameter meanings but lacks behavioral context, usage guidelines, and error handling. For a read operation with output schema, this is minimally adequate but leaves gaps in operational 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 0%, so the schema provides no parameter descriptions. The description adds basic semantics: project_id is '專案 ID 或路徑' (project ID or path) and mr_iid is 'MR 的 IID（專案內編號）' (MR's IID, project-internal number). This clarifies what the parameters represent but doesn't provide format examples, validation rules, or usage context. Baseline is 3 since it adds some value but doesn't fully compensate for the 0% 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 ('取得' meaning 'get' or 'retrieve') and the resource ('Merge Request 詳細資訊' meaning 'Merge Request detailed information'). It distinguishes from siblings like list_merge_requests (which lists multiple) and get_merge_request_changes/commits (which get specific aspects). However, it doesn't explicitly differentiate from all siblings in the description text.
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 use get_merge_request versus list_merge_requests (for single vs multiple), or versus get_merge_request_changes/commits (for full details vs specific aspects). No prerequisites or contextual usage hints are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool gets file changes/diffs, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, pagination, error conditions, or what format the diff is returned in (e.g., raw diff, parsed JSON). The description is minimal and lacks context about the tool's behavior 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 appropriately sized and front-loaded: the first sentence states the purpose clearly. The Args section is structured but minimal. There's no wasted text. However, it could be more structured with bullet points or clearer separation, and the translation mix (Chinese purpose, English parameter labels) is slightly inconsistent but not detrimental.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and simple parameters (2 required), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context (e.g., authentication, rate limits) and usage guidelines. For a read-only tool with output schema, it's adequate but could be more informative about when and how 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 0%, so the schema provides no parameter descriptions. The description adds basic semantics: 'project_id: 專案 ID 或路徑' (project ID or path) and 'mr_iid: MR 的 IID' (MR's IID). This clarifies that project_id can be an ID or path and mr_iid is an integer IID (not the global ID). However, it doesn't explain where to find these values, their formats, or examples. With 0% schema coverage, the description partially compensates but leaves gaps.
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: '取得 Merge Request 的檔案變更（diff）' (Get Merge Request file changes/diff). It specifies the verb ('取得' - get) and resource ('Merge Request 的檔案變更' - Merge Request file changes). It distinguishes from siblings like get_merge_request (which likely gets MR metadata) and get_merge_request_commits (which gets commits). However, it doesn't explicitly differentiate from compare_branches (which might also show diffs).
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 this tool is appropriate (e.g., for reviewing code changes before merging) or when not to use it (e.g., for getting MR metadata). It doesn't reference sibling tools like compare_branches (for branch diffs) or get_merge_request_commits (for commit lists). The only implicit context is that it's for MRs, but no explicit usage rules are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states what the tool does ('取得 Merge Request 包含的 commits') without describing return format, pagination, error conditions, authentication needs, or rate limits. For a read operation with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence states the purpose clearly, followed by a brief parameter list. There's no wasted text, and the structure (purpose then args) is logical. It could be slightly more polished but earns high marks for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and simple parameters, the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context (e.g., what the commits output looks like or error handling). For a read tool with output schema, it's passable but not comprehensive.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics: it explains 'project_id' as '專案 ID 或路徑' (project ID or path) and 'mr_iid' as 'MR 的 IID' (MR's IID), which clarifies data types beyond the schema. However, it doesn't detail format constraints (e.g., path syntax) or examples, leaving room for improvement given the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '取得 Merge Request 包含的 commits' (Get commits included in a Merge Request). It specifies the verb '取得' (get) and resource 'commits' with context 'Merge Request'. However, it doesn't explicitly differentiate from sibling tools like 'get_commit' or 'list_commits', which reduces it from 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 sibling tools like 'get_merge_request' (which might return commit info) or 'list_commits' (which lists commits more broadly), nor does it specify prerequisites or exclusions. The only context is implicit from the tool name and parameters.
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 only states the basic function without mentioning whether this is a read-only operation, what permissions are required, whether results are paginated (implied by parameters but not explicitly stated), rate limits, or error conditions. The description adds minimal behavioral context beyond the bare function.
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 appropriately concise with a clear purpose statement followed by a parameter list. The structure is front-loaded with the main function first. However, the parameter section uses generic labels without additional explanatory text, which keeps it brief but could be more informative.
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 that there's an output schema (which handles return values), no annotations, and 4 parameters with 0% schema coverage, the description provides the basic function but lacks important context. It doesn't explain behavioral aspects, usage guidelines, or parameter details that would help an agent use this tool effectively alongside its many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an Args section that lists all 4 parameters with brief Chinese labels, but with 0% schema description coverage, this provides only basic parameter identification. It doesn't explain parameter semantics, formats, constraints, or relationships. The description compensates somewhat by naming the parameters, but doesn't add meaningful semantic context beyond what's minimally required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as '列出專案的分支' (list project branches), which is a specific verb+resource combination. It distinguishes itself from siblings like 'get_branch' (singular) and 'compare_branches', but doesn't explicitly differentiate from other list operations like 'list_commits' or 'list_merge_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 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 use 'list_branches' versus 'get_branch' (for a single branch) or 'compare_branches', nor does it provide any context about prerequisites or typical use cases.
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 tool 'browses' which implies read-only behavior, but doesn't explicitly state this. It doesn't disclose important behavioral traits like authentication requirements, rate limits, pagination behavior, error conditions, or what happens with invalid parameters. The parameter documentation is basic and doesn't explain behavioral implications.
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 appropriately sized with a clear purpose statement followed by parameter documentation. The structure is logical with purpose first, then parameters. While efficient, the parameter documentation could be more integrated with the purpose statement rather than appearing as a separate Args section.
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 that there's an output schema (which handles return values), no annotations, and 4 parameters with 0% schema coverage, the description provides basic purpose and parameter documentation but lacks important context. For a file browsing tool, it should explain what the output contains (files vs directories, metadata included), how recursion affects results, and error scenarios. The presence of an output schema reduces but doesn't eliminate the need for behavioral 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?
With 0% schema description coverage, the description provides basic parameter documentation in the Args section, explaining what each parameter represents (project ID, directory path, branch/tag reference, recursion flag). However, it doesn't add meaningful semantic context beyond what's obvious from parameter names - no format examples, constraints, or interaction effects. For 4 parameters with no schema descriptions, this provides minimal compensation.
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 '瀏覽 Repository 檔案結構' (browse repository file structure), which is a specific verb+resource combination. It distinguishes itself from siblings like list_branches or list_commits by focusing on the file tree structure rather than version control entities. However, it doesn't explicitly contrast with tools like get_commit which might also provide file information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. While the purpose is clear, there's no mention of when this tool is appropriate compared to siblings like list_commits (which might show file changes) or get_commit (which might include file details). The description only documents parameters without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the action ('合併 Merge Request') without explaining critical behaviors: whether this is a destructive write operation, what permissions are required, how conflicts are handled, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves the agent guessing about important operational aspects.
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 appropriately sized and front-loaded with the core purpose first. The Args section is organized efficiently with one line per parameter. There's no wasted text, though the structure could be slightly improved by integrating parameter explanations more naturally into the description rather than as a separate section.
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 this is a mutation tool with no annotations, 4 parameters (2 required), and an output schema exists, the description is moderately complete. It covers the basic action and parameters but lacks crucial context about behavioral traits, error conditions, and usage prerequisites. The existence of an output schema means return values are documented elsewhere, but the description should still address mutation consequences and operational constraints.
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 0%, so the description must compensate. It provides brief explanations for all 4 parameters in the Args section, adding meaning beyond the bare schema. However, the explanations are minimal ('專案 ID 或路徑' = 'project ID or path') and don't clarify format expectations, constraints, or practical usage examples. The description adds some value but doesn't fully bridge the schema coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('合併' meaning 'merge') and resource ('Merge Request'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'create_merge_request' or 'update_merge_request' by specifying the merge action. However, it doesn't explicitly differentiate from other merge-related operations like 'approve_merge_request' beyond the core action.
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., MR must be approved or pipeline must pass), conditions for successful merging, or what happens in conflict scenarios. Given siblings like 'approve_merge_request' and 'update_merge_request', the lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('retry') but doesn't describe what 'retry' entails (e.g., re-executes a failed job, resets status, may have side effects), authentication requirements, rate limits, or what happens if the job isn't retriable. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief and front-loaded with the core purpose ('重試單一 Job'). The Args section is structured but minimal. There's no wasted text, though it could be more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and simple parameters, the description is minimally complete. However, for a mutation tool ('retry'), it lacks critical context like behavioral effects, error conditions, and usage distinctions from siblings, making it only adequate for basic 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 0%, so the schema provides no parameter descriptions. The description adds basic semantic labels ('專案 ID 或路徑' for project_id, 'Job ID' for job_id) in Chinese, which helps clarify what each parameter represents. However, it doesn't explain format expectations (e.g., project path syntax), constraints, or examples, leaving gaps for the agent to interpret.
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 ('重試' meaning 'retry') and resource ('單一 Job' meaning 'single Job'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'retry_pipeline' or 'cancel_pipeline', which would require more specific context about what type of job is being retried.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., job must be in a failed state), when-not-to-use scenarios, or comparison to sibling tools like 'retry_pipeline' or 'get_job'. 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 the full burden of behavioral disclosure. While '建立新的 Merge Request' implies a write/mutation operation, the description doesn't address permissions required, side effects (e.g., notifications sent), error conditions, or what happens on success (e.g., MR ID returned). The parameter list adds some context but lacks behavioral details like rate limits or idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose statement, followed by a structured parameter list. However, the parameter explanations are minimal (single phrases), and the overall text could be more efficient by integrating usage context. It avoids redundancy but feels slightly sparse rather than optimally concise.
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 operation) and lack of annotations, the description is moderately complete. It covers the core action and parameters but misses behavioral details (e.g., permissions, notifications). The presence of an output schema (not provided here) might help, but without it, the description should ideally mention what's returned (e.g., MR object or ID).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a clear parameter list with brief explanations in Chinese (e.g., '專案 ID 或路徑' for project_id, '來源分支' for source_branch), adding meaningful semantics beyond the schema's generic titles. However, it doesn't explain format constraints (e.g., what constitutes a valid project_id path) or dependencies between parameters.
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: '建立新的 Merge Request' (create a new Merge Request). It specifies the verb (create/建立) and resource (Merge Request), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'merge_merge_request' or 'update_merge_request', which would require more specific language about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'merge_merge_request' (to complete a merge), 'update_merge_request' (to modify an existing one), and 'list_merge_requests' (to view existing ones), there's no indication of prerequisites, appropriate contexts, or distinctions between creation and other merge request operations.
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 pagination parameters (page, per_page) which hints at paginated results, but doesn't describe the return format, error conditions, rate limits, authentication requirements, or whether this is a read-only operation. The description is minimal and lacks behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with a clear purpose statement followed by parameter explanations. However, the structure could be improved by front-loading more critical information (like behavioral traits) rather than just listing parameters. The parameter section is useful but makes the description somewhat parameter-heavy relative to other context.
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 that there's an output schema (which handles return values), no annotations, and 5 parameters with good semantic coverage in the description, the description is moderately complete. However, it lacks important behavioral context (authentication, errors, rate limits) and usage guidance relative to sibling tools, leaving gaps for an AI agent.
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 description adds significant value beyond the schema, which has 0% description coverage. It provides Chinese translations and clarifies parameter purposes: '專案 ID 或路徑' (project ID or path) for project_id, '狀態篩選' (status filter) with enumerated values for status, '分支或標籤名稱篩選' (branch or tag name filter) for ref, and pagination context for page/per_page. This compensates well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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: '列出專案的 CI/CD Pipelines' (List project's CI/CD pipelines). It specifies the verb ('list') and resource ('CI/CD pipelines'), though it doesn't explicitly differentiate from sibling tools like 'get_pipeline' or 'list_pipeline_jobs'.
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_pipeline' (for single pipeline details) or 'list_pipeline_jobs' (for jobs within pipelines), nor does it specify prerequisites or contextual usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is an update operation but doesn't mention permission requirements, whether changes are reversible, rate limits, or what happens when only some fields are provided. The description lacks crucial behavioral context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief with a clear title and parameter explanations. However, the structure mixes Chinese and English ('Args:' header), and the parameter explanations could be more efficiently integrated. It's functional but not optimally structured for quick scanning.
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 this is a mutation tool with 8 parameters, no annotations, but with an output schema present, the description is moderately complete. The parameter explanations are helpful, but it lacks behavioral context about permissions, side effects, and error conditions. The output schema reduces the need to describe return values, but more operational guidance would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides essential parameter semantics through the Chinese annotations in the Args section. It explains what each parameter represents (project ID/path, MR IID, new title, new description, etc.) and clarifies format details like '逗號分隔' (comma-separated) for reviewer_ids. This significantly compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 '更新 Merge Request' (update Merge Request), which is a specific verb+resource combination. It distinguishes from siblings like create_merge_request (creation) and get_merge_request (read), but doesn't explicitly differentiate from merge_merge_request (final merging) or other update-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing merge request), when to use create_merge_request instead, or how this differs from merge_merge_request. 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 for behavioral disclosure. It mentions that 'last_lines' displays only the last N lines (with 0 meaning all), which adds some context about output behavior. However, it lacks critical details: whether this is a read-only operation, authentication needs, rate limits, error conditions, or what the output schema contains. For a tool with no annotations, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the purpose is stated first in a single sentence, followed by a structured 'Args:' section. There's no wasted text, and each part earns its place. Minor points are deducted because the 'Args:' formatting could be more integrated, but overall it's efficient.
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 no annotations, 0% schema coverage, but an output schema exists, the description is minimally adequate. It covers the tool's purpose and parameter semantics well, but lacks behavioral context (e.g., safety, errors) and doesn't leverage the output schema to explain return values. For a tool with three parameters and no annotations, it should do more to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all three parameters: 'project_id' as project ID or path, 'job_id' as Job ID, and 'last_lines' with a clear explanation (last N lines, 0 for all, default 0). This goes beyond the schema's basic titles, providing essential context for proper usage, though it doesn't cover all edge cases (e.g., format of project path).
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: '取得 Job 的執行日誌' (Get job execution logs). It specifies the verb ('取得' - get) and resource ('Job 的執行日誌' - job execution logs), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_job' or 'retry_job', 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, context (e.g., after a job runs), or comparisons to siblings like 'get_job' (which might return job metadata) or tools for pipeline logs. Usage is implied only through parameter descriptions, not explicit guidelines.
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 detailed information but doesn't describe what 'detailed information' includes (e.g., metadata, settings, statistics), whether it's a read-only operation, potential errors (e.g., invalid project_id, access denied), or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise and front-loaded, with the core purpose stated first ('取得 GitLab 專案詳細資訊') followed by parameter details. Both sentences are necessary and add value—no redundant or verbose language. However, the structure could be slightly improved by integrating the parameter explanation more seamlessly rather than as a separate 'Args:' section.
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 low complexity (1 parameter) and the presence of an output schema (which should define return values), the description is minimally adequate. It covers the purpose and parameter semantics but lacks behavioral details (e.g., error handling, authentication needs) and usage guidelines. With no annotations, it doesn't fully compensate for these gaps, making it incomplete for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'project_id' can be either a numeric ID or a path string (e.g., 'group/project'), clarifying the parameter's purpose and acceptable formats. This compensates well for the schema's lack of descriptions, though it doesn't detail constraints like path syntax rules.
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 ('取得' meaning 'get' or 'retrieve') and resource ('GitLab 專案詳細資訊' meaning 'GitLab project detailed information'), making the purpose immediately understandable. It distinguishes itself from siblings like 'list_projects' by focusing on retrieving detailed information for a specific project rather than listing multiple projects. However, it doesn't explicitly contrast with other get_* tools (e.g., get_branch, get_merge_request) beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication, project access), differentiate from similar tools like 'list_projects' for bulk retrieval, or specify use cases (e.g., for viewing project settings, metadata). The agent must infer usage from the tool name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 checking connection status but doesn't describe what constitutes a successful check, what response format to expect, whether it requires authentication, or any rate limits. The description is minimal and lacks operational details.
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—a single sentence that directly states the tool's function without any fluff or redundant information. Every word contributes to understanding the purpose, making it efficiently front-loaded.
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 simplicity (no parameters, has output schema), the description is minimally adequate but lacks depth. It doesn't explain what the health check entails or what the output might indicate, though the presence of an output schema reduces the need to detail return values. For a diagnostic tool, more context about failure modes or interpretation would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose without unnecessary detail.
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 checking connection status to a GitLab server, using specific verbs ('健康檢查', '確認') and identifying the target resource. It doesn't explicitly differentiate from siblings like 'server_info', but the focus on connectivity rather than general server information provides some implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'server_info' or other diagnostic tools. It states what the tool does but offers no context about appropriate use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions pagination parameters ('page', 'per_page'), which hints at paginated results, but doesn't describe the return format, rate limits, authentication needs, or whether it's read-only. For a list tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a clear purpose statement followed by parameter explanations. It uses bullet points for parameters, making it easy to scan. There's minimal waste, though the structure could be slightly improved by integrating the purpose more fluidly with the args.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, 1 required), no annotations, and an output schema present, the description does a decent job. It explains the purpose and parameters well, and since an output schema exists, it doesn't need to detail return values. However, it lacks behavioral context like pagination behavior or error handling, which would be helpful for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that explains each parameter's purpose, such as 'project_id: 專案 ID 或路徑' (project ID or path) and 'state: 狀態篩選' (state filter). With schema description coverage at 0%, this adds substantial value beyond the schema, clarifying semantics for all 4 parameters. However, it doesn't detail enum values for 'state' beyond listing them, slightly limiting completeness.
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: '列出專案的 Merge Requests' (List project's Merge Requests). It specifies the verb ('列出' - list) and resource ('Merge Requests'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get_merge_request' (singular) or 'list_merge_request_notes', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_merge_request' for single MRs or 'list_merge_request_notes' for notes, nor does it specify prerequisites or contexts for usage. The only implied usage is listing merge requests, but no explicit guidelines are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information and connection status, implying a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, error conditions, or what specific information is returned. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: '取得 GitLab MCP 服務器資訊和連線狀態'. It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple, parameter-less tool. Every part of the sentence contributes directly to understanding the tool's 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?
Given the tool's simplicity (0 parameters, no annotations, but with an output schema), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, usage context, or output specifics. The presence of an output schema means the description doesn't need to explain return values, but it should still cover more about when and how to use the tool effectively. This results in a score of 3, indicating a basic but incomplete description.
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 doesn't need to explain parameters, so it appropriately focuses on the tool's purpose. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce any confusion about inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '取得 GitLab MCP 服務器資訊和連線狀態' (Get GitLab MCP server information and connection status). It specifies the verb ('取得' - get) and resource ('GitLab MCP 服務器資訊和連線狀態'), but doesn't explicitly differentiate it from the sibling 'health_check' tool, which might serve a similar purpose. The description is specific enough to understand what the 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 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 any prerequisites, context for usage, or comparisons with sibling tools like 'health_check'. The agent must infer usage from the purpose alone, which is insufficient for optimal 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 of behavioral disclosure. It mentions pagination and search filtering, which is useful, but lacks critical details: it doesn't specify authentication requirements, rate limits, error conditions, or whether it's a read-only operation (though 'list' implies non-destructive). For a tool with no annotations, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with a clear purpose statement, followed by a bullet-point-like 'Args' section that efficiently documents parameters. Every sentence earns its place, though it could be slightly more front-loaded by integrating parameter details more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, but with an output schema), the description is reasonably complete. It covers the purpose and all parameters in detail. Since an output schema exists, it doesn't need to explain return values. However, it lacks behavioral context (e.g., auth, errors), which slightly reduces completeness for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter in Chinese: 'search' for project name keywords, 'membership' to filter to joined projects (default True), 'page' for pagination (default 1), and 'per_page' for items per page (default 20, max 100). This fully compensates for the schema's lack of descriptions, providing clear semantics and constraints.
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: '列出可存取的 GitLab 專案' (List accessible GitLab projects). It specifies the resource (GitLab projects) and scope (accessible ones), though it doesn't explicitly differentiate from siblings like 'get_project' which retrieves a single project. The verb '列出' (list) is appropriate for this collection operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_project' (for single project details) or 'list_project_members' (for project members), nor does it specify prerequisites or contexts where this tool is preferred. 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.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![gitlab-mcp MCP server](https://glama.ai/mcp/servers/snowild/gitlab-mcp/badges/card.svg)](https://glama.ai/mcp/servers/snowild/gitlab-mcp)

Score Badge

Copy to your README.md:

[![gitlab-mcp MCP server](https://glama.ai/mcp/servers/snowild/gitlab-mcp/badges/score.svg)](https://glama.ai/mcp/servers/snowild/gitlab-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/snowild/gitlab-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server