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detonnate

careerproof-mcp

by detonnate

Find evidence gaps

careerproof_find_evidence_gaps

Re-runs job requirement matching to surface weakly supported requirements, each paired with a concrete suggestion for evidence to add.

Instructions

Re-runs requirement matching for a job and returns only the requirements with weak or unproven support, each with a concrete suggestion for what evidence to add.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesJob ID returned by careerproof_analyse_job_description
projectIdNo
candidateIdNo

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, the description carries the full burden. It usefully discloses that matching is re-run (implying recomputation/refresh of prior results) and describes the shape of the return (only failing requirements, each with a suggestion). However, it omits side effects, whether prior results are overwritten, required permissions, or whether a prior analyse_job_description/match_requirements run is mandatory.

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?

A single well-formed sentence with the core action and the distinguishing output scope front-loaded. No filler or redundancy.

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?

There is no output schema, so the description must explain return values; it does so partially (gaps plus a concrete suggestion for each). But with no annotations and two of three parameters undocumented, the definition stops short of fully equipping an agent to call the tool correctly in all cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% — jobId is documented in the schema (and echoed indirectly by 'for a job'), while projectId and candidateId are entirely undocumented in both schema and description. The description adds no meaning beyond the schema and does not compensate for the two unexplained optional parameters.

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 states a specific verb and resource ('re-runs requirement matching for a job') and precisely narrows the output scope ('only the requirements with weak or unproven support'), which distinguishes it from the sibling careerproof_match_requirements and careerproof_find_evidence without needing to open any schema.

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 rather than stated: the phrase 're-runs requirement matching' suggests this follows a prior analysis and complements match_requirements, but the description never explicitly says when to choose this tool over match_requirements or find_evidence. No prerequisites or exclusions are given.

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