query-understand

Parse natural-language data requests into structured request.json files.

Updated Mar 31, 2026
One-click install
npx skills add https://github.com/kamilseghrouchni/vcro-sourcing --skill query-understand
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: query-understand
Source: https://github.com/kamilseghrouchni/vcro-sourcing/tree/main/.claude/skills/query/understand
Command: npx skills add https://github.com/kamilseghrouchni/vcro-sourcing --skill query-understand

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill converts a free-text buyer request into a precise, machine-readable request.json that downstream discovery components can consume, reducing manual translation and errors.

Core Features & Use Cases

  • Parses natural-language requests into a structured brief with fields like request_text, original_text, and gaps.
  • Outputs a single, well-formed request.json to a designated path for use by the query layer.
  • Surface gaps and inferences explicitly so downstream skills can decide when to ask for clarification or proceed with defaults.
  • Use Case: A researcher asks for data on a given disease; the Skill produces a ready-to-use request.json that subsequent steps can act upon.

Quick Start

Provide a natural-language data request and the skill will generate request.json at the configured path.

Frequently Asked Questions about query-understand

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert a natural-language data request into a structured JSON format?

This skill parses a free-text buyer request into a precise, machine-readable request.json that downstream discovery components can consume. It converts natural-language requests into a structured brief, reducing manual translation and errors.

How to parse natural-language requests into structured briefs for downstream data discovery?

Provide a natural-language data request and the skill generates a ready-to-use request.json at a configured path. This structured brief drives downstream discovery, score, and deliver processes without manual translation.

Does the request-understand skill perform external API calls or access external wikis during parsing?

No, this natural-language parsing approach does not access external wikis or perform API calls. It focuses entirely on deterministic parsing and explicit inference to surface gaps, outputting a complete request.json based solely on the provided text.

What happens when there are gaps or missing information in a natural-language data request?

When gaps exist in a natural-language data request, the parsing process surfaces these inferences explicitly in the request.json. Downstream skills can then decide whether to ask for clarification or proceed with default values.

Why should I use a structured request.json instead of raw text for data discovery?

A structured request.json provides a precise, machine-readable brief that downstream query layers can consume directly, reducing manual translation errors. This standardizes the input for automated discovery, scoring, and delivery processes.