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by TechnoLaps

civify_parse_cv

Convert resume files (PDF, DOCX, images) into structured JSON with contact details, work experience, education, skills, and projects for further processing.

Instructions

Parse a resume document (PDF, DOCX, image) into structured JSON schema containing contact details, work experience, education, skills, and projects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoLanguage code (e.g. 'en', 'ar', 'auto'). Default is 'auto'.auto
file_pathYesAbsolute or relative file path to the resume document (PDF, DOCX, image).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose the output contents (contact, experience, education, skills, projects), which is useful given no output schema. However it says nothing about cost, authentication, file-size limits, or failure modes, and a sibling pricing tool suggests the operation is paid.

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?

A single front-loaded sentence with zero waste that names the input formats and the returned schema sections in one pass.

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?

Since no output schema exists, the description appropriately enumerates the returned fields, making it nearly self-sufficient for a 2-parameter parse tool. Only error behavior and size limits are absent.

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 description coverage is 100%, so both parameters are already documented. The description only echoes the format list from file_path and adds no extra meaning about language handling or path resolution.

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 (parse) and resource (resume document) plus the supported formats and the resulting structured fields. It is clearly the extraction tool among siblings like tailor_cv, score_ats, and mask_pii, though it never names those alternatives.

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 guidance on when to choose this tool over siblings such as civify_tailor_cv or civify_score_ats, nor any prerequisites (e.g., payment via civify_get_pay_per_cv_pricing). Usage must be inferred from the name alone.

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