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ffpy

GitLab MCP Code Review

by ffpy

reply_to_merge_request_discussion

Post responses to merge request discussions on GitLab to address code review feedback and collaborate on changes.

Instructions

Reply to a merge request discussion.

Args:
    project_id: The GitLab project ID or URL-encoded path
    merge_request_iid: The merge request IID (project-specific ID)
    discussion_id: The ID of the discussion to reply to
    body: The reply text
Returns:
    Dict containing the created note information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
merge_request_iidYes
discussion_idYes
bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The @mcp.tool()-decorated handler function that implements the logic to reply to a GitLab merge request discussion by creating a note on the specified discussion.
    @mcp.tool()
    def reply_to_merge_request_discussion(ctx: Context, project_id: str, merge_request_iid: str, discussion_id: str, body: str) -> Dict[str, Any]:
        """
        Reply to a merge request discussion.
        
        Args:
            project_id: The GitLab project ID or URL-encoded path
            merge_request_iid: The merge request IID (project-specific ID)
            discussion_id: The ID of the discussion to reply to
            body: The reply text
        Returns:
            Dict containing the created note information
        """
        gl = ctx.request_context.lifespan_context
        project = gl.projects.get(project_id)
        mr = project.mergerequests.get(merge_request_iid)
        discussion = mr.discussions.get(discussion_id)
        
        note = discussion.notes.create({'body': body})
        
        return note.asdict()
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.

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