Claude-skills code-to-prd

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

install
source · Clone the upstream repo
git clone https://github.com/alirezarezvani/claude-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/alirezarezvani/claude-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.gemini/skills/cmd-code-to-prd" ~/.claude/skills/alirezarezvani-claude-skills-code-to-prd && rm -rf "$T"
manifest: .gemini/skills/cmd-code-to-prd/SKILL.md
source content

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