github-pr-review-mcp

list_pending_review_comments

List all draft comments in the pending review for a pull request, including file path, line, side, and body. Returns an empty array if no pending review exists.

Instructions

List all draft comments in the pending review for the PR. Returns empty array if no pending review exists. Each comment includes path, line, side, body, and metadata.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "owner": "<owner>",
      "repo": "<repo>",
      "prNumber": "<prNumber>"
    },
    "name": "list_pending_review_comments"
  }
}

Input Schema

Name	Required	Description
`repo`	Yes	Repository name
`owner`	Yes	Repository owner/organization
`prNumber`	Yes	Pull request number

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.4Aug 30, 2026

TDQS

A4/5.0

Behavior4/5

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 reveals a key edge-case behavior (returns an empty array if no pending review exists) and lists the fields present in each comment (path, line, side, body, metadata), which is useful operational context beyond just the name.

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 compact and front-loaded. The first sentence states the core purpose, the second adds the empty-array behavior and return field summary. Every sentence earns its place with no fluff.

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?

There is no output schema, so the description reasonably explains the return shape (empty array if no pending review, and comment fields). It is sufficient for an agent to select and invoke the tool correctly, though 'metadata' is left unspecified and pagination/limits are not addressed.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already fully documents the three parameters (owner, repo, prNumber). The description adds no additional possible values, constraints, or relationships between parameters, so baseline 3 is appropriate.

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 states a specific action (list), the exact resource (draft comments in the pending review for the PR), and distinguishes it from sibling tools like get_pending_review which returns the review object itself. It also specifies the return context: empty array if no pending review exists.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes clear it lists draft comments in the pending review, which gives some contextual usage guidance. However, it does not explicitly contrast with closely related siblings like get_pr_comments, get_pending_review, or submit_pr_review, leaving the agent to infer when this tool is the right choice among them.

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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