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github_repo_signal

Count GitHub repos and sum top stars for any search query to gauge developer interest and competition.

Instructions

GitHub repo count and top-star sums for a search query (developer interest / competition proxy).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesGitHub search query

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.3.0

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 must carry the behavioral transparency burden. It discloses the operational output (repo count and top-star sums) and the semantic purpose. It does not mention query syntax expectations, limitations, rate limits, or whether results are live or cached, but the read-only nature is reasonably inferable from 'count and sums.'

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. It front-loads the concrete output and then adds the interpretive context in a parenthetical. Every word contributes meaning; there is no filler or redundancy.

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 one simple parameter, a high-level output description, and no output schema, the description is nearly complete. It tells the agent what will happen with the query and what the result represents. It would be more complete with a note on query formatting or a pointer to github_trend for comparison, but overall it covers the essentials.

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 describes the only parameter as 'GitHub search query' with 100% coverage, which sets the baseline at 3. The description adds the context that the query drives repo-count and star-sum calculations, but it does not provide additional syntax, formatting, or example guidance beyond the schema.

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 states what the tool does: it returns GitHub repo count and top-star sums for a search query. It frames the output as a developer interest/competition proxy, which adds meaning. It does not explicitly differentiate itself from siblings like github_trend, but the specific 'repo count and top-star sums' output is distinctive enough.

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 description implies the use case: measuring developer interest or competition via GitHub search. However, it gives no explicit guidance on when to prefer this tool over alternatives such as github_trend or hn_signal, and no exclusions or conditions are provided.

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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