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Job Application Agent MCP Server

Job Application Agent MCP Server

by Kirill-ark

score_match

Scores how well a vacancy fits your CV on a 0-100 scale, returning the score, label, matched skills, gaps, and a short explanation so you can prioritize the roles worth applying to.

Instructions

Score how well one vacancy fits the CV, from 0 to 100.

    Args:
        job_id: The `id` of a vacancy returned by search_jobs.

    Returns the score, a label (good >= 65, maybe >= 30, bad), matched
    skills, gaps and a short explanation. Results are cached.
    

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": {
      "job_id": "<job_id>"
    },
    "name": "score_match"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Adds real context beyond the annotations: results are cached (which explains the readOnlyHint=false despite this being a computational query), the score scale and the label thresholds (good >= 65, maybe >= 30, bad) are disclosed. It stops short of stating whether caching can return stale scores for an updated CV, which is the one behavioral caveat an agent would want.

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?

Front-loaded with the purpose and scale in the first line, then a compact param note and a compact return note. The 'Args:' docstring formatting is a minor artifact but costs almost nothing; every sentence conveys information.

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

Completeness5/5

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

For a one-parameter scoring tool with an output schema present, the description covers purpose, input provenance, output shape and caching behavior. Nothing an agent needs in order to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is 0%, so the description must carry the parameter meaning — and it does, identifying job_id as a vacancy `id` obtained from search_jobs and nothing else. The single parameter is fully accounted for; only value format (id shape) is left implicit.

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?

States a specific verb and resource ('score how well one vacancy fits the CV') with an explicit scale (0-100). This is clearly distinguishable from siblings like search_jobs and read_cv, which retrieve rather than evaluate.

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 usage by requiring a job_id 'returned by search_jobs', which establishes the correct call order. However, it never states when to prefer this tool over read_cv or draft_cover_letter, nor any conditions under which scoring is inappropriate (e.g., no CV uploaded).

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