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SalAkBuK

github-stars-mcp

by SalAkBuK

github_submit_worker_digest

Submit sub-agent digests for categorized repo analysis, validated against baseline taxonomy to prevent race conditions and handle GraphQL sync fallback.

Instructions

Map-Reduce Step 2: Allows sub-agents to submit their distilled category & pitch digest. Validates against baseline taxonomy, prevents reassigned worker race conditions, and handles GraphQL list sync fallback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
worker_idYesWorker ID submitting this digest (e.g. 'worker-1').
session_idYesThe active orchestration session identifier.
analyzed_reposYesList of repositories analyzed by this worker.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description must disclose behavioral traits, and it does: it validates against baseline taxonomy, prevents race conditions, and handles GraphQL list sync fallback. This goes beyond a simple 'submit' and informs the agent of side effects and safeguards. However, it does not mention error handling, idempotency, or what the response indicates, which would be useful for a mutation-like operation.

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, dense sentence that front-loads the step number and core action, then adds critical behavioral constraints. Every clause adds value: the step context, the submit action, validation, race conditions, and fallback. No filler or repetition.

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

Completeness3/5

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

For a submission tool with no output schema and no annotations, the description covers the core action and key behaviors but omits important operational details such as the expected response (success/failure), what happens on validation failure, and any prerequisites (e.g., session state). Given the tool's role in a multi-step workflow, an agent might need more guidance on post-submission expectations.

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%, so all parameters (worker_id, session_id, analyzed_repos) are already documented with their types and purposes. The description adds minimal new semantic meaning; it references 'distilled category & pitch digest' which aligns with the schema but does not enrich parameter details further. Baseline 3 is appropriate when the schema carries the full load.

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?

The description clearly states it is the submission step for distilled category and pitch digests in a map-reduce workflow. It mentions specific responsibilities (validation, race condition prevention, GraphQL fallback) that distinguish it from orchestration, reduction, and assignment tools in the sibling list. The verb 'submit' and resource 'worker digest' are explicit.

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?

The description situates this as 'Map-Reduce Step 2' and notes it is for sub-agents to submit their digests, implying it is used after analysis and before reduction. It does not explicitly list alternative tools or when not to use it, but the pipeline context provides clear situational guidance. A small gap is the lack of explicit exclusions or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.