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Command

/code-to-prd

Reverse-engineer a frontend codebase into a PRD. Usage: /code-to-prd [path]

From plugin
alirezarezvani-claude-skills
26k150 skills116 agents150 commands2 MCP
Install
$ npx -y skills add alirezarezvani/claude-skills --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/code-to-prd

Context preview

What this command does when you run it.

Reverse-engineer a frontend codebase into a PRD. Usage: /code-to-prd [path]

Command definition

code-to-prd.md
name: code-to-prd
description: "Reverse-engineer a frontend codebase into a PRD. Usage: /code-to-prd [path]"
argument-hint: "[path]"

/code-to-prd

Reverse-engineer a frontend codebase into a complete Product Requirements Document.

Usage

/code-to-prd                    # Analyze current project
/code-to-prd ./src              # Analyze specific directory
/code-to-prd /path/to/project   # Analyze external project

What It Does

1. **Scan** — Run `codebase_analyzer.py` to detect framework, routes, APIs, enums, and project structure 2. **Scaffold** — Run `prd_scaffolder.py` to create `prd/` directory with README.md, per-page stubs, and appendix files 3. **Analyze** — Walk through each page following the Phase 2 workflow: fields, interactions, API dependencies, page relationships 4. **Generate** — Produce the final PRD with all pages, enum dictionary, API inventory, and page relationship map

Steps

Step 1: Analyze

Determine the project path (default: current directory). Run the frontend analyzer:

python3 {skill_path}/scripts/codebase_analyzer.py {project_path} -o .code-to-prd-analysis.json

Display a summary of findings: framework, page count, API count, enum count.

Step 2: Scaffold

Generate the PRD directory skeleton:

python3 {skill_path}/scripts/prd_scaffolder.py .code-to-prd-analysis.json -o prd/

Step 3: Fill

For each page in the inventory, follow the SKILL.md Phase 2 workflow:

  • Read the page's component files
  • Document fields, interactions, API dependencies, page relationships
  • Fill in the corresponding `prd/pages/` stub

Work in batches of 3-5 pages for large projects (>15 pages). Ask the user to confirm after each batch.

Step 4: Finalize

Complete the appendix files:

  • `prd/appendix/enum-dictionary.md` — all enums and status codes found
  • `prd/appendix/api-inventory.md` — consolidated API reference
  • `prd/appendix/page-relationships.md` — navigation and data coupling map

Clean up the temporary analysis file:

rm .code-to-prd-analysis.json

Output

A `prd/` directory containing:

  • `README.md` — system overview, module map, page inventory
  • `pages/*.md` — one file per page with fields, interactions, APIs
  • `appendix/*.md` — enum dictionary, API inventory, page relationships

Skill Reference

  • `product-team/code-to-prd/skills/code-to-prd/SKILL.md`
  • `product-team/code-to-prd/skills/code-to-prd/scripts/codebase_analyzer.py`
  • `product-team/code-to-prd/skills/code-to-prd/scripts/prd_scaffolder.py`
  • `product-team/code-to-prd/skills/code-to-prd/references/prd-quality-checklist.md`
Read more
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