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detonnate

careerproof-mcp

by detonnate

Find evidence

careerproof_find_evidence

Search stored evidence—commits, pull requests, docs and claims—by keyword to find interview proof. Each result includes a confidence tag so callers know how much to trust it.

Instructions

Free-text search across all stored evidence (commits, pull requests, docs, dependency manifests, CV claims and manual notes). Every result carries its confidence tag (verified / inferred / user_claim / missing) so the caller knows how much to trust it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesText to search for in evidence excerpts and file paths
projectIdNoRestrict the search to one project

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?

No annotations are provided, so the description carries the full burden. It does disclose a valuable behavioral trait not in the schema: every result carries a confidence tag (verified/inferred/user_claim/missing), which tells the caller how much to trust hits. However, it says nothing about ranking, pagination, result volume, or performance characteristics of a cross-corpus search.

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?

Two sentences, zero filler, and the scoping statement (all stored evidence) is front-loaded ahead of the return-value note. Every clause earns its place.

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?

No output schema exists, and the description usefully covers the return shape (results tagged with confidence levels), which is the main thing an agent needs to interpret output. It is slightly incomplete on the undocumented limit parameter and on how results are ordered when many match, but is otherwise solid for a 3-param search tool.

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 67% – query and projectId are documented in the schema, while limit is not. The description adds no parameter-level detail beyond the schema (no ranking, ordering, or limit defaults), so it neither compensates for the undocumented limit nor enriches the documented ones. Baseline 3 for mid-range coverage is appropriate.

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?

States a specific verb and resource ('Free-text search across all stored evidence') and enumerates the searched corpora (commits, PRs, docs, manifests, CV claims, notes), which is far more than a restatement of the name. It does not explicitly distinguish itself from the sibling careerproof_find_evidence_gaps, so an agent must infer the boundary rather than read it.

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 a discovery use case (searching stored evidence) but never states when to reach for this tool versus find_evidence_gaps, match_requirements, or the add_* tools, and gives no exclusions or prerequisites. Usage is inferable from the verb but not spelled out.

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