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get_pull_request_comments

Retrieve review comments from a specific pull request on GitHub. Input the repository owner, repository name, and pull request number to access detailed feedback and discussions.

Instructions

Get the review comments on a pull request

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYesRepository owner (username or organization)
pull_numberYesPull request number
repoYesRepository name

Implementation Reference

  • The core handler function that fetches review comments for a pull request using the GitHub API and parses the response with Zod.
    export async function getPullRequestComments(
      owner: string,
      repo: string,
      pullNumber: number
    ): Promise<z.infer<typeof PullRequestCommentSchema>[]> {
      const response = await githubRequest(
        `https://api.github.com/repos/${owner}/${repo}/pulls/${pullNumber}/comments`
      );
      return z.array(PullRequestCommentSchema).parse(response);
    }
  • index.ts:191-194 (registration)
    Tool registration in the MCP server's list of tools, including name, description, and input schema reference.
      name: "get_pull_request_comments",
      description: "Get the review comments on a pull request",
      inputSchema: zodToJsonSchema(pulls.GetPullRequestCommentsSchema)
    },
  • MCP server dispatcher case that parses arguments, calls the getPullRequestComments handler, and formats the response.
    case "get_pull_request_comments": {
      const args = pulls.GetPullRequestCommentsSchema.parse(request.params.arguments);
      const comments = await pulls.getPullRequestComments(args.owner, args.repo, args.pull_number);
      return {
        content: [{ type: "text", text: JSON.stringify(comments, null, 2) }],
      };
    }
  • Zod input schema defining parameters for the get_pull_request_comments tool: owner, repo, pull_number.
    export const GetPullRequestCommentsSchema = z.object({
      owner: z.string().describe("Repository owner (username or organization)"),
      repo: z.string().describe("Repository name"),
      pull_number: z.number().describe("Pull request number")
    });
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 but offers minimal information. It doesn't mention whether this is a read-only operation, what permissions might be required, whether results are paginated, or what format the comments are returned in. For a data retrieval tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the tool's core function without any wasted words. It's appropriately sized for a straightforward data retrieval tool and gets directly to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'review comments' encompasses versus regular comments, doesn't indicate the return format or structure, and provides no context about authentication requirements or rate limits. The agent would be left guessing about important implementation details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with all three parameters clearly documented in the schema itself. The tool description adds no additional parameter information beyond what's already in the schema descriptions, so it meets but doesn't exceed the baseline expectation when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('review comments on a pull request'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_pull_request_reviews' or 'get_pull_request_files', which could cause confusion about what specific type of pull request data this tool retrieves.

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 'get_pull_request_reviews' and 'get_pull_request_files' available, there's no indication of what distinguishes this tool (comments) from those other pull request data retrieval tools, leaving the agent to guess based on tool names 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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