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Aayat AI

Repo health ($0.005)

repo-health
Read-only

Health report for any public GitHub repository: stars, forks, open issues, last push, latest release and release cadence, commits and active committers in 90 days (bus factor), licence, archived/fork status, community profile and OpenSSF Scorecard, with a verdict (healthy/ok/stale/abandoned), score and reasons. Price: $0.005 in USDC per call (x402 or prepaid credits). In the free trial.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesGitHub repository: owner/name or https://github.com/owner/name.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
repoYes
flagsYesReasons behind the verdict (level, code, message).
forksNo
scoreYes0-100.
starsYes
isForkNo
licenceNoSPDX id.
partialYesTrue if some details could not be fetched.
sourcesNo
verdictYes
archivedYes
checkedAtNo
createdAtNo
scorecardNoOpenSSF Scorecard (0-10) with per-check scores.
lastPushAtYes
openIssuesNoOpen issues plus pull requests.
descriptionNo
defaultBranchNo
latestReleaseNo
releasesLastYearNo
commitsLast90DaysNoCommits on the default branch in 90 days (counted up to 100).
communityHealthPercentNoGitHub community profile: README, licence, contributing guide, code of conduct...
activeCommittersLast90DaysNoDistinct committers in those commits (bus factor).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true, idempotentHint=false), so the bar is lower. The description adds genuinely non-derivable context: the $0.005 USDC cost, the x402/prepaid-credits payment mechanism, the free-trial availability, and the four-tier verdict plus score/reasons output. It does not discuss rate limits or failure behavior for invalid/private repos.

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 purpose, followed by a dense but orderly enumeration of returned signals and then pricing. Two sentences, no filler; the long signal list is information-bearing rather than padding, though the single sentence is quite packed.

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?

An output schema exists, so return values need not be spelled out — and the description still gives an accurate summary of them. With annotations covering safety and the schema covering the sole input, an agent has everything needed to decide and invoke correctly, including commercial constraints.

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% for the single 'repo' parameter, which already documents both accepted forms (owner/name or full URL). The description adds nothing about the parameter, so the baseline of 3 applies.

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?

States a specific verb+resource ('Health report for any public GitHub repository') and enumerates the exact signals returned, from stars and forks through bus factor and OpenSSF Scorecard. This clearly distinguishes it from sibling tools like dependency-report, package-audit, or license-check, which cover narrower slices.

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?

Usage is implied by the content (use it when you want an overall repo health verdict), but there is no explicit when-to-use/when-not guidance and no routing to alternatives such as changelog, dependency-report, or package-audit for narrower questions. The only explicit condition given is scope: 'any public GitHub repository'.

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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