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Is this repo OK?

check_repo
Read-onlyIdempotent

Checks a public GitHub repo: every package its lockfiles pin at its latest commit, in every folder and 14 ecosystems (npm, PyPI, crates.io, Go, Maven, NuGet, RubyGems, Packagist, Pub, Swift, Hex, Hackage, CRAN, Julia), against every known flaw. Says the answer on the site's scale (yes, mostly, kind-of, no; unknown when it holds no lockfile we can read), what to update first and what each flaw lets someone do, in plain words. A first look at a big repo takes a few seconds.

Input Schema

NameRequiredDescriptionDefault
fullNoAlso every flaw of every package (hundreds of KB for a big repo). Without it: the answer, what to update and why, and where the full list is.
repoYesowner/name, or the repo's GitHub URL: vercel/next.js, https://github.com/pallets/flask

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, so the bar is lower, yet the description still adds latency expectations, the degraded 'unknown' outcome when no lockfile is parseable, and what the response contains at a high level. It doesn't discuss rate limits or failures on private/missing repos, leaving minor gaps.

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-loaded with the core operation and then layered with scope, output meaning, and latency. Dense and nearly waste-free, though the ecosystem list and long compound sentences make it heavier than necessary.

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 carries the burden of explaining return values and does so: the four-level scale plus 'unknown', the prioritization guidance, plain-language exploit impact, and where the full list lives. Nothing an agent needs to call and interpret this correctly is missing.

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% and both parameters are well documented in the schema, including the size trade-off of 'full'. The description adds no additional parameter guidance beyond reinforcing that the default answer is summarized. Baseline 3 is appropriate when the schema carries this much weight.

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?

Specific verb and resource: 'Checks a public GitHub repo', immediately narrowed by scope (lockfiles at latest commit, every folder, 14 named ecosystems). This is clearly distinguishable from check_stack and the incident-oriented siblings, which deal with different objects entirely.

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 clear applicability boundaries: public repos only, needs a readable lockfile, and 'unknown' otherwise. It also signals cost ('a first look at a big repo takes a few seconds') which helps an agent decide when to invoke. It does not, however, name check_stack or explain when that alternative should be preferred.

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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