prompt-to-spec-converter

Converts user requests into executable engineering specifications with goals and acceptance criteria.

3|Updated Jun 8, 2026

Search Tags:#feature development #specification #engineering practices #specification writing #request clarification

Ready to run

npx skills add https://github.com/pax-k/pax-fullstack-harness --skill prompt-to-spec-converter

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-to-spec-converter
Source: https://github.com/pax-k/pax-fullstack-harness/tree/main/skills/prompt-to-spec-converter
Command: npx skills add https://github.com/pax-k/pax-fullstack-harness --skill prompt-to-spec-converter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of converting vague product or engineering requests into clear, executable specifications, ensuring a solid foundation for development without ambiguity.

Core Features & Use Cases

Spec Conversion: Turn ambiguous requests into complete specifications with goals, non-goals, requirements, and acceptance criteria.
Contextual Research: Incorporate research on product docs, architecture, and existing specs.
Validation: Ensure acceptance criteria are testable and assumptions are explicit.
Use Case: When a feature request is too broad, use this Skill to create a detailed spec for implementation, reducing the risk of misinterpretation.

Quick Start

Use the prompt-to-spec-converter skill to generate a spec for a new feature request 'asynchronous data fetching'.

Frequently Asked Questions about prompt-to-spec-converter

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

FAQPage Schema

How do I convert a vague feature request into an executable specification?▼

An executable specification transforms ambiguous product requests into structured engineering tasks by defining goals, non-goals, requirements, and acceptance criteria. It reduces misinterpretation risks for cross-cutting features by validating assumptions and incorporating contextual research.

When do I need to write a detailed specification for a feature request?▼

You need to write a detailed specification when a feature request is too broad, ambiguous, risky, or cross-cutting. Generating a comprehensive spec clarifies the scope and constraints, ensuring the engineering team handles complex tasks without misinterpretation.

How to ensure acceptance criteria are testable when writing engineering specs?▼

To ensure acceptance criteria are testable when writing engineering specs, make all assumptions explicit and validate them against user context and constraints. Transforming requests into executable specifications requires careful validation steps to confirm criteria are concrete and measurable.

Can I use a spec converter for asynchronous data fetching implementation?▼

Yes, you can use a spec converter for asynchronous data fetching implementation to turn a broad request into a detailed specification. It structures the engineering task by defining goals, non-goals, requirements, and testable acceptance criteria for the new feature.