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Tangled MCP Server

Tangled MCP Server

by zzstoatzz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_repo_pulls

List pull requests you created in a repository. Specify the repo in 'owner/repo' format and optionally set a limit between 1 and 100. Only returns PRs authored by you.

Instructions

list pull requests created by the authenticated user for a repository

note: only returns PRs that the authenticated user created (tangled stores PRs in the creator's repo, so we can only see our own PRs).

Args: repo: repository identifier in 'owner/repo' format limit: maximum number of pulls to return (1-100)

Returns: ListPullsResult with list of pull requests

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>"
    },
    "name": "list_repo_pulls"
  }
}

Input Schema

NameRequiredDescriptionDefault
repoYesrepository identifier in 'owner/repo' format (e.g., 'zzstoatzz/tangled-mcp')
limitNomaximum number of pulls to return

Output Schema

NameRequiredDescriptionDefault
pullsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.0.12

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description adequately explains the behavioral limitation (only own PRs) and the reason (PRs stored in creator's repo). It does not explicitly state it is read-only, but the context implies a safe operation. Returns a ListPullsResult, which is detailed in the output schema.

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 structured with a clear statement, a note, and an Args section. It is slightly verbose due to the note, but every sentence adds value. Could be more concise without losing clarity.

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

Completeness5/5

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

Given the presence of an output schema, the description covers the purpose, parameter details, and an important behavioral limitation. No critical information is missing for an agent to correctly select and invoke this 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 coverage is 100%, so the schema already describes both parameters (repo format, limit range). The description repeats the format and adds a note about the repo identifier, but does not add significant new meaning beyond what the schema provides. For high coverage, this is acceptable but not exceptional.

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?

Description clearly states the tool lists pull requests created by the authenticated user, and explicitly distinguishes it by noting the scope limitation (only own PRs). This separates it from sibling tools like list_repo_issues.

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 note about only returning PRs created by the authenticated user provides important context for when to use this tool, but does not explicitly mention alternatives or when not to use it. The rationale is given, which helps in decision-making.

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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