skills.rest
auldsyababua
auldsyababuaCOMMUNITY
Explore all skills by this author →
GitHub

prd-creator

Convert and validate Product Requirements Documents into a hybrid Markdown+YAML format.

6|1|Updated Nov 12, 2025
Search Tags:#product management#validation#agent development#PRD#AI safety#requirements engineering#product requirements#LLM-native
One-click install
npx skills add https://github.com/auldsyababua/instructor-workflow --skill prd-creator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prd-creator
Source: https://github.com/auldsyababua/instructor-workflow/tree/main/skills/prd-creator
Command: npx skills add https://github.com/auldsyababua/instructor-workflow --skill prd-creator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyYAML, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the critical need for Product Requirements Documents (PRDs) that are not only human-readable but also machine-interpretable and safety-focused for AI agent development. It prevents common AI agent misbehaviors like hallucination, context poisoning, and constraint violations by enforcing strict, structured requirements.

Core Features & Use Cases

  • LLM-Native PRD Creation: Generates new PRDs from scratch using a hybrid Markdown+YAML format optimized for AI agent consumption.
  • Existing PRD Conversion & Validation: Converts legacy PRDs into the LLM-native format and validates existing PRDs against compliance standards, ensuring safety and completeness.
  • Safety-First Design: Incorporates critical safety elements like llm_directives (low temperature, explicit persona), Technical Constraints (forbidden patterns), and Out of Scope sections to control agent behavior.
  • Use Case: A product manager needs to define a new feature for an AI-driven development team. This skill can help create a PRD that explicitly guides the AI agents, preventing them from building unintended features or violating security protocols.

Quick Start

Create a new PRD for a user authentication system, ensuring it includes security constraints and defines out-of-scope features.

Frequently Asked Questions about prd-creator

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

FAQPage Schema
How do I create a PRD that AI agents can safely interpret and execute?▼

Machine-readable PRDs use structured Markdown+YAML formats with explicit constraints, unique identifiers, and atomic acceptance criteria to prevent AI hallucination and context poisoning. This Skill converts or generates PRDs in LLM-native format, enforcing safety directives and forbidden patterns so agents follow requirements precisely.

What's the difference between a standard PRD and an LLM-native format?▼

LLM-native PRDs combine human-readable Markdown with machine-parseable YAML, adding safety layers like `llm_directives` (temperature, persona), technical constraints, and out-of-scope sections. Standard PRDs lack the structured ambiguity controls needed for safe AI agent consumption.

Can I convert an existing PRD into a format AI agents can use?▼

Yes. This Skill validates and converts legacy PRDs into the LLM-native hybrid format, applying safety checks and ensuring compliance with structured requirements. The result is machine-interpretable while remaining human-readable.

What safety controls does an LLM-native PRD enforce?▼

LLM-native PRDs enforce low-temperature reasoning, explicit personas, forbidden patterns, token-efficient constraints, and atomic acceptance criteria. Forward-chaining validation prevents constraint violations, mesa-optimization, and unintended agent behaviors.

Do I need special tools to work with Markdown and YAML requirements documents?▼

This Skill handles the hybrid Markdown+YAML structure and validation automatically. PyYAML is the only dependency, enabling parsing and validation of the structured format without additional tooling.

When should I use a structured PRD format for AI agent development?▼

Use LLM-native PRDs whenever AI agents consume requirements directly—product feature development, safety-critical workflows, or any scenario where ambiguity could cause unintended agent behavior or constraint violations.

Related Skills

Explore More Product & Management Skills→
MaVoid-TeamMaVoid-Team

release-notes

Convert tickets and changelogs into structured markdown release notes.

Official
Intermediate
asalhamedasalhamed

product-owner

Draft PRDs and acceptance criteria from stakeholder inputs using MoSCoW and RICE frameworks.

Community
Advanced
adiytharpansaadiytharpansa

ai-agent-helper

Optimize AI agent prompts, task decomposition, and tool selection workflows.

Community
Intermediate
bibo1243bibo1243

shared-rules

Coordinate two AI bots to enforce conversational etiquette and priority rules.

Community
Intermediate