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SkillMapper MCP Server

SkillMapper MCP Server

by VishweshMurali
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

retrieve_evidence

Fetches resume evidence supporting a specific job requirement by matching resume and job IDs, returning relevant passages for comparison.

Instructions

Retrieve resume evidence supporting a specific job requirement.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "resume_id": "<resume_id>",
      "job_id": "<job_id>",
      "requirement": "<requirement>"
    },
    "name": "retrieve_evidence"
  }
}

Input Schema

NameRequiredDescriptionDefault
top_kNo
job_idYes
resume_idYes
requirementYes

Output Schema

NameRequiredDescriptionDefault
evidenceYes
requirementYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. Beyond implying a read operation with 'Retrieve,' it does not state permissions, rate limits, or any other behavioral trait.

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

Conciseness4/5

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

The single sentence is front-loaded and contains no filler, earning its place. However, it may be too terse for a tool with four parameters and no schema descriptions, so it is not maximally well-sized.

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?

An output schema exists, so return values need not be explained. But with no annotations and 0% schema description coverage, the description is insufficiently complete: it omits usage context and parameter semantics needed to invoke the tool correctly.

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 0%, so the description must explain the parameters, but it only vaguely connects to 'requirement' and 'resume.' It does not clarify resume_id, job_id, or top_k, leaving most parameter semantics undocumented.

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 ('Retrieve') and resource ('resume evidence') scoped to a job requirement. It is clear but does not differentiate itself from sibling tools like compare_resume_to_job or search_documents.

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 guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The description only states what it does, leaving the agent to infer its role among the sibling tools.

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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