GitLab MCP Code Review

by ffpy

Overview Schema Related Servers Score Discussions

Python

Hybrid

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes focused on merge request management and code review workflows, with clear boundaries between actions like adding comments, approving, and comparing versions. However, there is some potential overlap between 'add_merge_request_comment' and 'add_merge_request_discussion' as both involve commenting, though the latter is more specific to file positions.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern throughout, such as 'add_merge_request_comment', 'approve_merge_request', and 'fetch_code_review_rules'. All tools use snake_case and maintain a predictable structure, making them easy to parse and understand.
Tool Count5/5
With 12 tools, the set is well-scoped for a GitLab code review server, covering essential operations like fetching merge requests, managing discussions, approvals, and project searches. Each tool serves a clear purpose without redundancy, fitting the domain appropriately.
Completeness4/5
The toolset provides comprehensive coverage for code review tasks, including fetching rules, listing and fetching merge requests, adding and managing discussions, and handling approvals. A minor gap is the lack of tools for directly modifying merge requests (e.g., updating or merging them), but core review workflows are well-supported.
Average 3.3/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but doesn't mention critical behaviors: whether this requires specific permissions (e.g., merge request approver role), if it's idempotent (can you approve multiple times?), what happens on success/failure, or any rate limits. The return value is mentioned but not explained, though an output schema exists.
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 with clear sections (Args, Returns) and uses minimal sentences. Every sentence earns its place by providing essential information. However, the core purpose statement is overly terse and could benefit from slightly more context 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's moderate complexity (3 parameters, mutation action) and lack of annotations, the description is minimally adequate but has clear gaps. It covers parameters and return type at a high level, and an output schema exists to detail returns. However, it misses behavioral context (permissions, idempotency) and usage guidelines, which are important for a mutation tool in a collaborative system like GitLab.
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 all three parameters with brief explanations, adding value beyond the bare schema. However, it doesn't clarify important semantics: what format 'project_id' accepts (numeric ID vs. path), what 'IID' means, or how 'approvals_required' interacts with existing approval rules. The coverage is partial but not comprehensive.
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 ('a merge request'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'unapprove_merge_request' beyond the obvious verb difference, nor does it explain what 'approving' entails in GitLab's context (e.g., adding an approval vote).
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 'unapprove_merge_request' or other merge request operations. The description lacks context about prerequisites (e.g., user permissions, merge request state) or typical workflows, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool 'compare[s] two commits/branches/tags' and returns a 'Dict containing the comparison information,' but fails to describe critical behaviors: whether this is a read-only operation, potential rate limits, authentication needs, error conditions, or what specific information is included in the comparison (e.g., diffs, statistics). For a tool with no annotation coverage, this leaves significant 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 sized and well-structured: a clear purpose statement followed by a formatted list of arguments and returns. Each sentence earns its place by conveying essential information without redundancy. It could be slightly more front-loaded by emphasizing the tool's core function earlier, 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 the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameters adequately, and the presence of an output schema means it doesn't need to detail return values. However, it lacks behavioral context (e.g., safety, performance) and usage guidelines, which are important for an agent to invoke it correctly in a GitLab environment with sibling tools.
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 value by explaining each parameter: 'project_id: The GitLab project ID or URL-encoded path,' 'from_sha: The source commit/branch/tag,' and 'to_sha: The target commit/branch/tag.' This clarifies the semantics beyond just the parameter names. However, it doesn't provide format examples, validation rules, or constraints, keeping it at a baseline level.
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: 'Compare two commits/branches/tags to see the differences between them.' This specifies the verb ('compare') and resources ('commits/branches/tags'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'fetch_merge_request' or 'get_project_merge_requests', which might also involve version-related operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for comparison (e.g., code reviews, debugging), or exclusions. Given sibling tools like 'fetch_merge_request' that might retrieve similar data, the lack of differentiation leaves the agent without clear usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the action ('Delete') and return type ('Dict containing the status of the deletion'), but lacks critical details like required permissions, whether deletion is reversible, rate limits, or error conditions. This is a significant gap for a destructive operation.
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 with clear sections (Args, Returns) and uses bullet points for parameters, making it easy to scan. It's concise with no redundant information, though it could be slightly more front-loaded by emphasizing the destructive nature earlier.
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 (destructive operation with 3 parameters), no annotations, and an output schema (which covers return values), the description is moderately complete. It explains the action and parameters but lacks behavioral context like permissions or side effects, which is a notable gap for a deletion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all three parameters with brief explanations (e.g., 'The GitLab project ID or URL-encoded path'), adding basic semantics beyond the schema's titles. However, it doesn't provide format examples, constraints, or how to obtain these IDs, leaving room for improvement.
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 ('Delete') and resource ('a merge request discussion'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'resolve_merge_request_discussion' or 'reply_to_merge_request_discussion', 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?
No guidance is provided on when to use this tool versus alternatives like 'resolve_merge_request_discussion' or 'add_merge_request_discussion'. The description only states what it does, not when it's appropriate or what prerequisites might be needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Reply to') which implies a write operation, but doesn't disclose permissions required, rate limits, whether replies are editable/deletable, or how the discussion thread behaves. The mention of returning 'Dict containing the created note information' hints at a creation outcome, but lacks detail on response structure or error conditions. 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 efficiently structured with a clear purpose statement followed by parameter and return value sections. Every sentence serves a purpose: the first states the tool's function, and the subsequent lines document inputs/outputs. It avoids redundancy and is appropriately sized for a tool with four parameters. Minor improvement could come from integrating usage 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 the tool's moderate complexity (4 parameters, mutation operation) and lack of annotations, the description is minimally complete. It covers the basic purpose and parameters, and the presence of an output schema means it doesn't need to detail return values. However, for a write operation with siblings, it should include more behavioral context and usage guidance to be fully 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 all four parameters with brief explanations, adding meaning beyond the bare schema (e.g., clarifying that 'merge_request_iid' is project-specific). However, it doesn't explain parameter formats (e.g., what constitutes a valid 'project_id' or 'discussion_id'), constraints, or examples. The value added is marginal but covers basics, meeting the minimum viable baseline.
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 ('Reply to') and target resource ('a merge request discussion'), which is specific and unambiguous. It distinguishes this tool from siblings like 'add_merge_request_comment' or 'add_merge_request_discussion' by focusing on replying to existing discussions rather than creating new ones. However, it doesn't explicitly contrast with 'resolve_merge_request_discussion', which is a related but different operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing discussion), contrast with sibling tools like 'add_merge_request_comment' (for general comments) or 'resolve_merge_request_discussion' (for closing discussions), or specify scenarios where this tool is appropriate. 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 mentions the return type ('A list of projects') but doesn't disclose critical behavioral traits like whether this is a read-only operation, authentication requirements, rate limits, pagination, or error handling. For a search tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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. The Args/Returns structure is clear, though slightly verbose for a single parameter. Every sentence adds value, with no wasted words.
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 one parameter, no annotations, and an output schema exists (so return values needn't be explained), the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks behavioral context and usage guidelines, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaningful context: it explains that 'project_name' is for searching by name and clarifies that 'If None, returns all projects.' This compensates somewhat for the schema gap, though it doesn't detail format or constraints. With one parameter, this meets the baseline expectation.
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 'Search for GitLab projects by name,' which is a specific verb+resource combination. However, it doesn't differentiate this search tool from sibling tools that also interact with projects (like get_project_merge_requests), so it doesn't reach the highest 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 when this search is appropriate compared to other project-related tools or what contexts it's best suited for, leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return type ('List of merge request objects') but lacks critical details: authentication requirements, rate limits, pagination behavior (beyond the 'limit' param), error handling, or whether it's read-only (implied by 'Get' but not confirmed). The description is minimal and misses key operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, using bullet-like sections ('Args:', 'Returns:') for clarity. Each sentence adds value: the purpose statement, parameter explanations, and return type. There's no redundant information, though it could be slightly more front-loaded by integrating key details into the opening sentence.
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 context: 3 parameters, 0% schema description coverage, no annotations, but an output schema exists (implying return values are documented elsewhere). The description covers purpose and parameters adequately but lacks behavioral context (e.g., auth, rate limits) and sibling differentiation. It's minimally viable for a read operation but incomplete for safe and effective use without additional structured data.
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 semantics beyond the input schema, which has 0% description coverage. It explains 'project_id' as 'The GitLab project ID or URL-encoded path', clarifies 'state' with possible values ('all, opened, closed, merged, or locked'), and defines 'limit' as 'Maximum number of merge requests to return'. This compensates well for the schema's lack of descriptions, though it doesn't detail defaults (e.g., 'state' defaults to 'all', 'limit' to 20).
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: 'Get all merge requests for a project.' It specifies the verb ('Get') and resource ('merge requests for a project'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'fetch_merge_request' (singular) or 'search_projects', which could retrieve similar data in different contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'fetch_merge_request' (for a single MR) or 'search_projects' (which might include MRs), nor does it specify prerequisites (e.g., authentication needs) or exclusions (e.g., when not to use it). Usage is implied by the purpose but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 action ('resolve or unresolve') but lacks critical details: whether this requires specific permissions, if it's reversible, rate limits, or side effects. The return statement is vague ('updated discussion information'), leaving behavior unclear. 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 well-structured and front-loaded with the core purpose, followed by parameter explanations and return info. It's efficient with minimal waste, though the return statement could be more specific. Every sentence adds value, making it appropriately concise for a 4-parameter 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's moderate complexity (4 parameters, mutation action) and no annotations, the description is partially complete. It covers the purpose and parameters well, and an output schema exists (not detailed in context), reducing the need to explain return values. However, it lacks behavioral context (e.g., permissions, reversibility) and usage guidelines, leaving gaps for an AI agent to operate effectively.
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 context: 'project_id' as 'GitLab project ID or URL-encoded path', 'merge_request_iid' as 'project-specific ID', 'discussion_id' as 'ID of the discussion', and 'resolved' as 'True to resolve, False to unresolve'. This clarifies each parameter's role beyond the schema's basic titles. However, it doesn't cover format details (e.g., IID format), keeping it from a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Resolve or unresolve a merge request discussion.' It specifies the verb ('resolve/unresolve') and resource ('merge request discussion'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'delete_merge_request_discussion' or 'reply_to_merge_request_discussion', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing discussion), exclusions, or comparisons to siblings like 'delete_merge_request_discussion' for removal or 'add_merge_request_discussion' for creation. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits such as required permissions, whether this action is reversible, rate limits, or what specific 'unapproval information' is returned. The mention of returning a dict is minimal and lacks detail.
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 appropriately sized and front-loaded, with the purpose stated first, followed by parameter and return sections. Every sentence adds value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and an output schema exists, the description provides basic parameter semantics and mentions a return dict, which is adequate. However, for a mutation tool with no annotations, it lacks details on permissions, side effects, and error handling, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists both parameters with brief explanations, adding meaning beyond the schema's titles. However, it doesn't clarify format details (e.g., URL-encoded path examples) or IID specifics, leaving some 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 verb ('Unapprove') and resource ('a merge request'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'approve_merge_request' beyond the obvious opposite action, missing explicit comparison.
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 approval first), context (e.g., role-based permissions), or when to choose this over other merge request operations like commenting or fetching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It mentions the tool 'Adds' (implying a write operation) and returns 'Dict containing the created comment information', but doesn't disclose important traits like whether this requires specific permissions, if comments are editable/deletable, rate limits, or how it handles errors. The description doesn't contradict annotations (none exist), but fails to provide adequate behavioral transparency 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by parameter and return value sections. Every sentence adds value: the first states what the tool does, and the subsequent lines document inputs and outputs without redundancy. The formatting with 'Args:' and 'Returns:' headers enhances readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and no annotations, the description does well documenting parameters but lacks behavioral context for a mutation tool. The presence of an output schema means the description doesn't need to detail return values, but it should provide more guidance on usage and permissions. It's minimally adequate but has clear gaps in behavioral transparency.
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 for all three parameters beyond the schema's 0% coverage. It explains that 'project_id' can be 'ID or URL-encoded path', clarifies 'merge_request_iid' as 'project-specific ID' (not global ID), and specifies 'body' as 'comment text'. This compensates well for the schema's lack of descriptions, though it doesn't provide format examples or 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 action ('Add a general comment') and target resource ('to a merge request'), making the purpose immediately understandable. It distinguishes from siblings like 'add_merge_request_discussion' by specifying 'general comment' rather than discussion threads, though it doesn't explicitly contrast with other comment-related tools like 'reply_to_merge_request_discussion'.
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 when to choose 'add_merge_request_comment' over 'add_merge_request_discussion' or 'reply_to_merge_request_discussion', nor does it specify prerequisites like authentication or permissions needed to comment on merge requests.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states that the tool fetches a merge request and its contents, which implies a read-only operation, but doesn't disclose other behavioral traits like authentication needs, rate limits, error handling, or what specific contents are included. The prerequisite call adds some context but doesn't fully describe the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured: it starts with a clear purpose statement, follows with an important usage note in a separate paragraph, and then lists parameters and returns in a formatted way. Every sentence adds value without waste, making it easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of fetching merge requests with 2 parameters, no annotations, and no output schema, the description is partially complete. It covers purpose, usage guidelines, and parameters, but lacks details on behavioral aspects, return format specifics beyond 'XML string', and how it differs from siblings. The prerequisite note helps, but more context is needed for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists the two parameters (project_id and merge_request_iid) in the Args section, providing basic semantics that they are required for fetching. However, it doesn't add detailed meaning beyond naming them, such as explaining what an IID is or providing examples, leaving gaps in understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'fetch' and the resource 'GitLab merge request and its contents', making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_project_merge_requests' which might also retrieve merge requests, though the focus on a specific MR is implied.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance with the IMPORTANT note: 'You MUST call fetch_code_review_rules BEFORE using this tool to understand the team's code review standards and guidelines.' This clearly indicates a prerequisite and when to use this tool in relation to another specific sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool fetches via SSH and mentions possible outcomes (success with content, simple message if SSH not configured, error dict on connection failures). However, it lacks details on authentication requirements, rate limits, or what 'SSH is not configured' entails. The description doesn't contradict annotations, but could be more comprehensive given the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with three sentences that each add value: the first states the purpose, the second provides usage guidelines, and the third outlines return behavior. There is no wasted text, and key information is front-loaded.
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 (involves SSH and fetching rules), no annotations, no output schema, and 0 parameters, the description does a good job covering purpose, usage, and basic behavioral outcomes. However, it could be more complete by detailing authentication, error handling specifics, or format of returned content, which would help an agent use it more effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on behavior and usage. This meets the baseline for zero parameters, as it doesn't mislead or omit necessary param info.
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: 'Fetch the team's code review rules from a remote server via SSH.' This specifies the verb (fetch), resource (code review rules), and method (SSH). However, it doesn't explicitly differentiate from sibling tools like 'fetch_merge_request' or 'get_project_merge_requests', which might also retrieve data but for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'You should call this tool BEFORE reviewing any merge requests or code changes to understand the team's code review standards and guidelines.' This clearly indicates when to use it (as a prerequisite for code review activities) and implies alternatives (e.g., not using it would mean reviewing without standards).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly indicates this is a write operation ('Add'), but lacks details on permissions required, rate limits, error conditions, or whether the discussion is editable/deletable. The example in the position parameter adds some behavioral context but doesn't cover broader operational traits.
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 with a clear purpose statement followed by Args and Returns sections. The position example is detailed but necessary for understanding. It could be slightly more concise by integrating the example more tightly, but overall it's front-loaded and efficient.
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 with nested objects) and no annotations, the description does a good job explaining parameters and indicating a dict return. However, it lacks details on authentication, error handling, or side effects, which would be helpful for a mutation tool with no output schema details beyond 'Dict'.
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 schema description coverage is 0%, so the description must compensate. It provides detailed explanations for all 4 parameters, including a comprehensive example for the complex 'position' parameter with required fields, allowed values, and GitLab version specifics, adding significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Add a discussion'), target resource ('to a merge request'), and precise location ('at a specific position in a file'), distinguishing it from sibling tools like add_merge_request_comment (general comment) and reply_to_merge_request_discussion (reply to existing discussion).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'at a specific position in a file,' suggesting this tool is for file-specific discussions rather than general comments. However, it doesn't explicitly state when to use this versus alternatives like add_merge_request_comment or when not to use it (e.g., for non-file discussions).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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