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Parse a resume / CV

parse_resume
Read-onlyIdempotent

Convert resume text or local PDF/DOCX/TXT files into structured JSON with contact details, title, seniority, experience, education, and skills.

Instructions

Parse a resume into structured JSON: contact details, current title, seniority, job function, experience, education and skills. Give either the text or a local file path (PDF with a text layer, DOCX or TXT, max 5 MB; no OCR). Nothing is stored.

Input Schema

NameRequiredDescriptionDefault
textNoThe resume as plain text
file_pathNoPath to a local PDF, DOCX or TXT file

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world, so the description earns credit for adding constraints the annotations can't express: 5 MB cap, PDFs must have a text layer, no OCR, and 'Nothing is stored'. These are exactly the preconditions that would otherwise cause silent failure. It stops short of describing failure behavior when a scanned PDF or oversized file is passed.

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, front-loaded with the purpose and return shape, followed by the input contract and the single most important caveat (no OCR) and privacy note. No filler or repetition of the title.

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?

With only two simple params, full schema coverage, and rich annotations, the definition covers what an agent needs: output shape, accepted inputs, size/format limits, and that nothing is persisted. Minor gap: no guidance on what happens if both text and file_path are supplied, or on error responses.

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 100%, so baseline is 3, but the description adds genuine meaning beyond the schema: the 'either/or' exclusivity of text vs file_path is not encoded in a oneOf/anyOf, and the accepted file types, 5 MB limit, and no-OCR rule elaborate on the terse 'Path to a local PDF, DOCX or TXT file'.

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 (parse) plus resource (resume/CV) and immediately enumerates the output fields (contact details, title, seniority, function, experience, education, skills), so the agent knows exactly what comes back. The name plus this enumeration distinguishes it cleanly from siblings like match_resume_to_job or predict_match, which consume rather than extract resume data.

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 sentence 'Give either the text or a local file path' implies the two input modes and their mutual exclusivity, which is useful invocation guidance. However, it never states when to prefer this tool over parse_job_posting or when to hand results to match_resume_to_job, so the workflow positioning is only implied.

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