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GitHub Candidate Scorer

github_candidate_scorer
Read-only

Score and rank GitHub developers for a role with AI — skills, activity and fit…. Score and rank GitHub developers for a role with AI — skills, activity and fit — turning profiles into a shortlist for recruiters.

Input Schema

NameRequiredDescriptionDefault
inputNoInput for GitHub Candidate Scorer. See https://apify.com/noniner/github-candidate-scorer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only that output is a recruiter-facing shortlist, but says nothing about required auth, rate limits, or what data is fetched from GitHub — modest added value against a lowered bar.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is essentially the same sentence duplicated ('Score and rank GitHub developers for a role with AI — skills, activity and fit') with only a trailing clause added on the second copy. This is redundant padding rather than front-loaded precision.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex AI scoring tool with an opaque nested input object and no output schema. The description explains neither what inputs are required (e.g., a role spec or GitHub handles) nor what the scoring produces, leaving an agent unable to invoke it correctly.

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 nominally 100%, but the only parameter is an opaque nested 'input' object whose description is just a documentation URL, adding no real field meaning. The tool description itself provides zero parameter guidance, so it neither compensates nor detracts. Baseline 3.

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 gives a specific verb+resource ('score and rank GitHub developers') with a stated goal ('for a role', 'skills, activity and fit'), so an agent can grasp the function immediately. However it does nothing to distinguish itself from sibling tools like github_repo_analyzer or b2b_talent_sourcing_brief, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use, no when-not-to-use, and no named alternative among the many recruiting/GitHub siblings. Usage is only weakly implied by the phrase 'turning profiles into a shortlist for recruiters'.

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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