Skip to main content
Glama
VishweshMurali

SkillMapper MCP Server

compare_resume_to_job

Compare a resume against a job description using retrieval and LLM analysis to assess fit. Returns cached results unless a rerun is forced.

Instructions

Run the full resume-vs-job comparison agent (retrieval + LLM compare + retry/escalation). Expect 30s-several minutes on a local 8B model; returns a cached completed result unless force_rerun=True.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes
resume_idYes
force_rerunNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
job_idYes
statusYes
verdictYes
evidenceNo
reasoningYes
resume_idYes
confidenceYes
created_atNo
retries_usedNo
overall_scoreYes
matched_skillsNo
missing_skillsNo
escalation_reasonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it discloses two high-value traits: long and variable latency (30s-several minutes on a local 8B model) and default cache-return behavior. It omits cost/auth and whether results are deterministic, but covers the operationally critical facts well.

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 tight sentences, zero waste, with the pipeline scope front-loaded and the latency/caching caveat following. 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?

An output schema exists, so return values need not be described. The description supplies the latency, caching, and force_rerun context an agent needs to call it correctly; only auth/permission prerequisites are unaddressed, which is minor for this operation.

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 coverage is 0%, so the description must compensate. It explains force_rerun=True semantics (bypasses the cached result), which is the only non-obvious parameter; resume_id and job_id are self-explanatory by name. It adds some meaning but not full documentation for the coverage gap.

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 names a specific verb+resource ('Run the full resume-vs-job comparison agent') and enumerates the pipeline stages (retrieval + LLM compare + retry/escalation). It distinguishes the tool from siblings like retrieve_evidence by signaling it is the complete end-to-end operation, though it does not explicitly name a sibling.

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: this is the tool for a full comparison, and the caching note hints you need not rerun needlessly. However, it never states when to prefer it over retrieve_evidence or lookup_evaluation_result, nor any exclusions or prerequisites.

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