# AI Native Prd Architect

> Use when turning a feature idea into an implementation-ready PRD with traceable REQ IDs, acceptance criteria, NFRs, risks, data model, and task slices for /agileteam Phase 0.

- Skill: `dyai2025/ai-native-prd-architect` (Agent Skill)
- Install (CLI): `npx skillmds@latest add dyai2025/ai-native-prd-architect`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dyai2025/ai-native-prd-architect/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: DYAI2025 (https://skillmd.com/u/dyai2025)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/dyai2025/ai-native-prd-architect

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# AI-native PRD Architect

Produce a buildable, testable PRD without filling gaps by guessing.

## Workflow
1. Restate the goal and target repository.
2. Create stable `REQ-###` identifiers.
3. Define scope, non-goals, actors, data model, interfaces, constraints, NFRs, security/privacy risks, rollout and rollback notes.
4. Write Given/When/Then acceptance criteria for every REQ.
5. Build a traceability matrix with `REQ`, `test`, `task`, `evidence`, `wired-in-prod?`, and `evidence-class` columns.
6. Mark unknowns explicitly as `MISSING`, `OPEN QUESTION`, `ASSUMPTION`, or `BLOCKER`.

## Hard rules
- Never close a missing requirement through plausibility. Ask the user or call `brainstorming`.
- Every task must trace back to at least one REQ.
- Every REQ must have at least one machine-checkable acceptance signal.