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Repo AI-contribution preflight

repo_ai_policy
Read-onlyIdempotent

Before a coding agent opens a PR: does this GitHub repo ban, restrict or allow AI-assisted contributions? Reads AI_POLICY/CONTRIBUTING/AGENTS.md/PR template/SECURITY and returns a verdict, evidence lines with file:line, and build/test commands from AGENTS.md. Keyword heuristic: read the evidence. Price: $0.01 USDC on Base per call, paid with x402 (MCP transport: an unpaid call returns the x402 PaymentRequired object; retry with params._meta["x402/payment"]). Same tool over HTTP: GET /api/repo-ai-policy.

Input Schema

NameRequiredDescriptionDefault
repoYesowner/name or github.com URL (public repos)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld/idempotent annotations: it names the exact files read, the shape of the return (verdict, evidence lines with file:line, build/test commands), warns that the verdict is a keyword heuristic requiring evidence review, and discloses the $0.01 USDC x402 paywall plus the unpaid-call PaymentRequired retry path. That paywall disclosure is critical behavioral context an agent cannot get from annotations.

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?

Front-loads the core question and the trigger before the mechanics, and every clause carries information. It is dense and slightly run-on in the payment/pricing clause, but nothing is filler.

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?

With no output schema, the description correctly takes on the job of describing return values (verdict, file:line evidence, build/test commands) and explains the paid-call protocol and the equivalent HTTP endpoint. An agent has everything needed to invoke it and interpret the result.

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

Parameters4/5

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

The single `repo` parameter is fully documented in the schema (owner/name or URL, public repos), so the schema carries most of the load. The description adds one non-obvious detail the schema omits: the x402 payment is passed via params._meta["x402/payment"], which materially changes how the call is made.

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?

States a specific verb+resource: it reads a repo's AI_POLICY/CONTRIBUTING/AGENTS.md/PR template/SECURITY files and returns a verdict on whether AI-assisted contributions are allowed. That is far more specific than the name alone. It does not, however, differentiate itself from the sibling tool `policy`, which an agent could plausibly confuse with this one.

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?

Gives an explicit trigger: 'Before a coding agent opens a PR'. That is a clear usage context. It offers no exclusions or named alternatives (e.g., when to use `policy` instead), so it stops short of full routing guidance.

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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