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@jestay/bitbucket-mcp

@jestay/bitbucket-mcp

by jestays
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

list_pull_request_comments

List general and inline comments on a pull request to review existing feedback before posting new review comments. Paginated results help navigate through all comments.

Instructions

List the comments of a pull request (general and inline). Use it before posting review comments to avoid repeating observations already made. Paginated; next_page is set when more results exist.

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": {
      "repo": "<repo>",
      "pr_id": "<pr_id>"
    },
    "name": "list_pull_request_comments"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPage number (1-based).
repoYesRepository slug, e.g. "my-service" (not the full URL).
pr_idYesPull request id, e.g. 42.
pagelenNoResults per page (max 50, default 10).
workspaceNoWorkspace id. Optional when the BITBUCKET_WORKSPACE env var is set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the transparency burden. It adds useful behavioral details such as pagination ('Paginated; `next_page` is set when more results exist') and the inclusion of general and inline comments. However, it does not explicitly confirm that the operation is read-only, nor does it describe sorting or error 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 three sentences, all of which are relevant: main action, usage guidance, and pagination behavior. It is front-loaded with the purpose and contains no filler.

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?

The description covers purpose, usage, and pagination for a list tool with 5 parameters (fully schema-documented) and no output schema. It could be more complete by describing the return structure, but the information provided is sufficient for basic invocation and 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 100%, and the description adds no parameter-specific meaning beyond what the schema provides. The pagination mention relates to page/pagelen but does not add new syntax or format details.

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 tool's function: 'List the comments of a pull request (general and inline)'. This is a specific verb and resource, and it distinguishes itself from sibling tools like list_pull_requests, get_pull_request_diff, and create_pull_request_comment.

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 provides a clear usage context: 'Use it before posting review comments to avoid repeating observations already made.' This tells the agent when to use the tool, but it does not explicitly name alternatives or state when not to use it.

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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