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SkillMapper MCP Server

SkillMapper MCP Server

by VishweshMurali
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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search_documents

Search ingested resume and job-description chunks using hybrid BM25 and dense retrieval to find relevant evidence by query, section, or document type.

Instructions

Hybrid (BM25 + dense) search over ingested resume/job-description chunks.

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": {
      "query": "<query>"
    },
    "name": "search_documents"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
top_kNo
sectionNo
doc_typeNoany

Output Schema

NameRequiredDescriptionDefault
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It usefully discloses the hybrid BM25+dense ranking approach, which is real behavioral context beyond the schema, but says nothing about ranking behavior, result volume, or whether filtering happens before or after retrieval.

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?

A single front-loaded sentence with no filler, and the retrieval mechanism is stated up front. It is efficient, though arguably too terse given the undocumented parameters.

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 0% parameter coverage and no routing guidance versus four siblings, the description is not complete enough for an agent to call this correctly in a multi-tool retrieval set.

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 compensate and does not. Only 'query' is self-evident; 'section' and 'doc_type' are entirely undefined in both schema and description, and 'top_k' semantics (default 5, ranking cut) are unstated.

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 (search) and resource (ingested resume/job-description chunks) plus the retrieval technique (hybrid BM25 + dense). It does not distinguish itself from the sibling retrieve_evidence, which sounds like an overlapping retrieval tool, so the agent cannot tell them apart from the text alone.

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?

No when-to-use guidance, no conditions, no mention of alternatives such as retrieve_evidence or compare_resume_to_job. The agent is left to guess which retrieval tool fits a given task.

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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