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hyunwk

oss-trends-mcp

by hyunwk

Repository health and trend score

repo_health

Assess a GitHub repository's health by analyzing star momentum, maintenance freshness, npm/PyPI adoption, and HN buzz, then get a transparent 0-100 score breakdown.

Instructions

Deep signals for one github repository: star momentum, maintenance freshness, npm/PyPI adoption, HN buzz, plus a transparent 0-100 score breakdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesowner/name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that the tool computes a transparent 0-100 score breakdown and covers multiple signal types, which is useful. However, it omits operational details such as data freshness, rate limits, or whether it requires authentication, and it does not describe potential error conditions or output format beyond the score. This is a moderate gap for a tool with no annotation support.

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 a single, efficient sentence that front-loads the core purpose ('Deep signals for one github repository') and then lists specific signal categories and the score breakdown. Every clause adds meaningful information with no redundancy or filler. It is highly concise and well-structured.

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?

For a tool with only one parameter and no output schema, the description sufficiently conveys that it returns health-related signals and a transparent 0-100 score breakdown. It lists the types of signals (stars, maintenance, adoption, buzz), giving an agent a reasonable idea of the data returned. However, it does not specify the exact structure of the output or whether raw numeric values accompany the breakdown, which is a minor gap.

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?

The schema already provides 100% coverage for the sole parameter 'repo' with description 'owner/name'. The tool description does not add any additional semantic detail about the parameter, such as format examples or edge cases. Since schema coverage is high, the baseline of 3 is appropriate; the description offers no extra value for parameter understanding.

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?

The description clearly identifies the tool's purpose: providing deep signals for a single GitHub repository, listing specific signal categories (star momentum, maintenance freshness, adoption, buzz) and a score breakdown. It distinguishes from siblings by focusing on one repo's health rather than searching, recommending, or comparing. However, it lacks an explicit action verb like 'get' or 'analyze', which limits precision.

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?

The phrase 'for one github repository' implies it is for deep-diving a single repo, which hints at when to use it versus search_repos or compare_repos. However, there is no explicit guidance on when not to use it, no mention of alternatives, and no exclusions. The usage context is implied but not stated outright.

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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