create-prd
Interview the user about a product idea and write PRD.md. Use at the start of a new project,…
Review PRD.md for gaps, contradictions and unverifiable claims, write an improved PRD.md and record the findings in PRD-REVIEW.md.
$ npx -y skills add nurettincoban/ai-prd-workflow --skill verify-prd --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/verify-prdContext preview
The summary Claude sees to decide when to auto-load this skill.
Review PRD.md for gaps, contradictions and unverifiable claims, write an improved PRD.md and record the findings in PRD-REVIEW.md.
name: verify-prd description: "Review PRD.md for gaps, contradictions and unverifiable claims, write an improved PRD.md and record the findings in PRD-REVIEW.md." metadata: source: "https://github.com/nurettincoban/ai-prd-workflow" version: "3.0.0" checksum: "sha256:7d3332e5790aaaf1127e84d9d473f32eb8fe286f3f2058ad4a03fd3cb1f5d64f"
You are an expert product manager tasked with reviewing a Product Requirements Document (PRD). Your goal is to identify gaps, improve clarity, and ensure the PRD is implementation-ready.
Review `PRD.md` in the current directory and provide actionable feedback. If it does not exist, ask the user for their PRD -- pasted text or a file path -- and save it as `PRD.md` before proceeding.
Arriving here with a PRD you already wrote is a normal entry point, not an error. Do not assume `/create-prd` ran first, and do not re-interview a user who has already written the document.
Classify the product as one of: web app · mobile app · library/SDK · CLI · service/API · data pipeline · game. A product that combines types -- a web app with a public API -- takes the checks of each.
Then apply only the checks that fit. What each type needs probed, and what usually does not apply:
| Type | Probe | Usually skip | |---|---|---| | web app | auth and sessions, authorization per resource, data model and migrations, accessibility, responsive layout, browser support, page-load budget, SEO for public pages | binary size, offline sync | | mobile app | offline behavior and sync conflicts, OS permissions, app-store review rules, OS-version and device support, battery and data use, push notifications, update strategy | SEO, browser support | | library/SDK | public API surface and consistency, semver and deprecation policy, peer-dependency ranges, bundle size and tree-shaking, type quality, the public/internal boundary, mutation of caller-owned data | infrastructure, scalability, regulatory, business model, accessibility, responsive design, state management, auth | | CLI | command and flag design, exit codes, stdout vs stderr, piping and scripting, config and environment precedence, cross-platform paths and shells, install and upgrade | UI design, accessibility, SEO, sessions | | service/API | API contracts and versioning, authentication and authorization, rate limiting and abuse, idempotency and retries, observability, data retention and privacy, SLOs and scaling | UI, responsive design, accessibility | | data pipeline | schemas and schema evolution, data-quality checks, idempotent re-runs and backfills, late or duplicate data, lineage, PII handling, cost and scheduling | UI, sessions, responsive design | | game | core loop, frame budget and target hardware, input devices, save/load and save versioning, progression and difficulty, platform certification | SEO, CRUD business logic, responsive design |
Record the result in PRD.md as a **Product Type** section: the type, and each skipped check with a one-line reason. Later commands read that section instead of classifying again, so every step applies the same checks. Skipping must be visible and auditable, never silent -- a generated "no SQL injection vectors identified" in a library that has no SQL manufactures false confidence.
Before the gap analysis:
Identify critical missing elements in these areas:
1. PRODUCT FUNDAMENTALS
2. TECHNICAL REQUIREMENTS
3. BUSINESS CONSIDERATIONS
4. IMPLEMENTATION FACTORS
Provide specific recommendations in these areas:
1. STRUCTURE & CLARITY
2. COMPLETENESS & FEASIBILITY
3. PRIORITIZATION & IMPLEMENTATION
1. SUMMARY OF FINDINGS
2. SPECIFIC RECOMMENDATIONS
3. IMPROVED PRD
RFC-driven development for AI coding agents: idea or existing codebase → verified PRD → features → rules → sequenced RFCs → reviewed code. Agent Skills for Claude Code, Codex, Copilot, Cursor, Gemini CLI, OpenCode, Devin.
Repo: nurettincoban/ai-prd-workflow
Interview the user about a product idea and write PRD.md. Use at the start of a new project,…
Document an existing codebase as PRD.md, FEATURES.md and RULES.md, so new work is planned…
Turn PRD.md into FEATURES.md: permanent feature IDs, MoSCoW priorities, acceptance criteria…
Break the PRD into sequenced implementation RFCs under RFCs/ with an RFCS.md index, then…
Write RULES.md, the project standards the AI must follow, with registry-verified dependency…
Implement one RFC: check its predecessors, present a plan for approval, write the code, then…