A structured prompt pipeline that turns vague ideas into implementable RFCs — works with any AI assistant.
# Add to your Claude Code skills
git clone https://github.com/nurettincoban/ai-prd-workflowGuides for using ai agents skills like ai-prd-workflow.
Last scanned: 5/30/2026
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}ai-prd-workflow is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by nurettincoban. A structured prompt pipeline that turns vague ideas into implementable RFCs — works with any AI assistant. It has 273 GitHub stars.
Yes. ai-prd-workflow passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/nurettincoban/ai-prd-workflow" and add it to your Claude Code skills directory (see the Installation section above).
ai-prd-workflow is primarily written in Shell. It is open-source under nurettincoban on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh ai-prd-workflow against similar tools.
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Vague idea → verified PRD → features → rules → sequenced RFCs → reviewed, tested code
Quick Start · Workflow · Commands · Why RFCs? · Examples
RFC-driven since March 2025 — before planning modes existed in any AI coding agent.
A lightweight RFC-driven development workflow for AI coding tools. Ten battle-tested prompts take you from a rough idea to a verified PRD, prioritized features, project rules, and sequenced RFCs — then guide implementation, code review, and testing, one RFC at a time.
Use it two ways:
/create-prd, /implement-rfc 001, /workflow-status, …No CLI to learn, no framework to adopt, no lock-in. Just markdown.
curl -fsSL https://raw.githubusercontent.com/nurettincoban/ai-prd-workflow/main/install.sh | bash -s -- /path/to/your/project
Or from a clone:
git clone https://github.com/nurettincoban/ai-prd-workflow.git
cd ai-prd-workflow
./install.sh /path/to/your/project # both tools
./install.sh /path/to/your/project --claude # Claude Code only
./install.sh /path/to/your/project --cursor # Cursor only
Then open your project and work through the pipeline:
/create-prd # guided interview → PRD.md
/verify-prd # gap analysis → improved PRD.md
/extract-features # PRD.md → FEATURES.md (MoSCoW prioritized)
/generate-rules # → RULES.md (project standards for the AI)
/generate-rfcs # → RFCs/ folder, in strict implementation order
/implement-rfc 001 # plan → your approval → implementation
/review-rfc 001 # review the implementation against its spec
/test-strategy # comprehensive test plan
/manage-changes # requirements changed mid-build? assess impact first
/workflow-status # lost? see what's done and what's next
[!TIP] Cloning this repo and opening it in Claude Code or Cursor gives you the commands immediately — try them against the example project.
./copy-prompt.sh --list to browse)flowchart LR
IDEA([💡 Idea]) --> PRD[Create PRD] --> VERIFY[Verify PRD] --> FEAT[Extract Features] --> RULES[Generate Rules] --> RFCS[Generate RFCs]
RFCS --> IMPL[Implement RFC] --> REVIEW[Code Review] --> TEST[Test Strategy]
REVIEW -.->|next RFC| IMPL
CHANGE([Change request]) -.-> CM[Change Management] -.-> RFCS
When requirements change mid-development, run Change Management to assess impact before touching the docs, then continue. Run Workflow Status anytime to see where you are and what's next.
| Command | Prompt | Description |
|---|---|---|
/create-prd |
Interactive PRD Creation | Create a PRD through a guided step-by-step questioning process |
/verify-prd |
PRD Comprehensive Verification | Verify and improve your PRD by identifying gaps and quality issues |
/extract-features |
PRD to Features | Extract and organize features with MoSCoW prioritization |
/generate-rules |
PRD to Rules | Generate technical guidelines and standards for development |
/generate-rfcs |
PRD to RFCs | Break down your PRD into sequenced implementation units |
/implement-rfc <id> |
Implementation Template | Implement a single RFC — plan first, code after approval |
/review-rfc <id> |
Code Review | Review an implementation against RFC, rules, security, performance |
/test-strategy |
Testing Strategy | Generate a comprehensive test plan from features and RFCs |
/manage-changes |
PRD Change Management | Assess and integrate requirement changes mid-development |
/workflow-status |
Workflow Status | See which artifacts exist, detect drift, get the next step |
AI coding agents are strong enough now to build entire features unsupervised — which makes what you ask for the bottleneck, not the code. If you've heard of spec-driven development (GitHub Spec Kit, Amazon Kiro), this is the same philosophy — and this workflow predates both — with sequenced RFCs as the unit of work and no framework or CLI to adopt. Structured specs fix the real problems:
Yes — tactically. This workflow shipped in March 2025, before planning modes existed in any AI coding agent, and it solves a different problem than they do:
| Built-in plan mode | This workflow |
|---|---|
| Plans one task — "how do I implement this?" | Plans the product — what are we building, for whom, what's out of scope? |
| Plan dies with the session | PRD, features, rules, and RFCs persist across sessions, models, tools, and teammates |
| Takes your request at face value | /create-prd interviews you first — decisions leave your head before code exists |
| Reviews code by "looks right" | /review-rfc verifies against written acceptance criteria; /workflow-status catches drift |
The two compose rather than compete: /generate-rfcs decides what the next unit of work is, and each /implement-rfc hands your agent's planner a well-scoped, context-sized task — exactly what plan mode is good at.
Sweet spot: greenfield products, multi-week builds, and anyone building something real with AI — where scope creep and forgotten decisions, not code quality, are what kill the project. For a small fix in an existing codebase, your agent alone is fine. For everything bigger, write the spec first.
The examples/url-shortener folder contains complete sample outputs for each step of the workflow:
The prompts are plain markdown and work with any modern LLM:
Tool support:
install.sh)./copy-prompt.sh <prompt-file>)/implement-rfc exists for a reasonSee CONTRIBUTING.md for guidelines on submitting new prompts, quality standards, and testin