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A directory reorg added a skills/ path segment; hundreds of references never followed. This sweep repoints every path-like reference in SKILL.md, agents, commands, orchestration, and templates to verified on-disk targets: - 30 root commands + 19 root agents: missing skills/ segment inserted - 7 c-level persona agents: 17 hallucinated reference filenames substituted with the real files (e.g. okr_execution.md -> process_frameworks.md) - 5 research skills: phantom scripts/office/validate.py step replaced with a runnable stdlib zip-integrity check - email agents: skills frontmatter corrected to productivity/email - orchestration/ORCHESTRATION.md + templates: stale paths fixed; agent-template now requires trigger phrasing in descriptions (root cause) - 76 more files across engineering, c-level-advisor, compliance-os, research-ops, ra-qm, marketing, productivity; dual-publish pairs mirrored - dead refs dropped/replaced where no target ever existed (REGISTRY.md, trend_analyzer.py, cursor-microinteractions.md) New: scripts/check_paths.py linter (CI gate G1) + narrow allowlist for teaching examples. Verified: 540 files scanned, 0 unresolvable. https://claude.ai/code/session_019AJddAL1NADWMXsy1qNPQF
78 lines
2.6 KiB
Markdown
78 lines
2.6 KiB
Markdown
---
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name: code-to-prd
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description: Reverse-engineer a frontend codebase into a PRD. Usage: /code-to-prd [path]
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---
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# /code-to-prd
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Reverse-engineer a frontend codebase into a complete Product Requirements Document.
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## Usage
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```bash
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/code-to-prd # Analyze current project
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/code-to-prd ./src # Analyze specific directory
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/code-to-prd /path/to/project # Analyze external project
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```
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## What It Does
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1. **Scan** — Run `codebase_analyzer.py` to detect framework, routes, APIs, enums, and project structure
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2. **Scaffold** — Run `prd_scaffolder.py` to create `prd/` directory with README.md, per-page stubs, and appendix files
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3. **Analyze** — Walk through each page following the Phase 2 workflow: fields, interactions, API dependencies, page relationships
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4. **Generate** — Produce the final PRD with all pages, enum dictionary, API inventory, and page relationship map
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## Steps
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### Step 1: Analyze
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Determine the project path (default: current directory). Run the frontend analyzer:
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```bash
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python3 {skill_path}/scripts/codebase_analyzer.py {project_path} -o .code-to-prd-analysis.json
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```
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Display a summary of findings: framework, page count, API count, enum count.
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### Step 2: Scaffold
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Generate the PRD directory skeleton:
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```bash
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python3 {skill_path}/scripts/prd_scaffolder.py .code-to-prd-analysis.json -o prd/
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```
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### Step 3: Fill
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For each page in the inventory, follow the SKILL.md Phase 2 workflow:
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- Read the page's component files
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- Document fields, interactions, API dependencies, page relationships
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- Fill in the corresponding `prd/pages/` stub
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Work in batches of 3-5 pages for large projects (>15 pages). Ask the user to confirm after each batch.
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### Step 4: Finalize
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Complete the appendix files:
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- `prd/appendix/enum-dictionary.md` — all enums and status codes found
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- `prd/appendix/api-inventory.md` — consolidated API reference
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- `prd/appendix/page-relationships.md` — navigation and data coupling map
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Clean up the temporary analysis file:
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```bash
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rm .code-to-prd-analysis.json
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```
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## Output
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A `prd/` directory containing:
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- `README.md` — system overview, module map, page inventory
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- `pages/*.md` — one file per page with fields, interactions, APIs
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- `appendix/*.md` — enum dictionary, API inventory, page relationships
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## Skill Reference
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- `product-team/code-to-prd/skills/code-to-prd/SKILL.md`
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- `product-team/code-to-prd/skills/code-to-prd/scripts/codebase_analyzer.py`
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- `product-team/code-to-prd/skills/code-to-prd/scripts/prd_scaffolder.py`
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- `product-team/code-to-prd/skills/code-to-prd/references/prd-quality-checklist.md`
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