Agent skill

Code to PRD

by alirezarezvani in alirezarezvani/claude-skills

Reverse-engineers a frontend, backend or fullstack codebase into a product requirements document with per-page docs, an enum dictionary and an API inventory.

MITAuto-check passedProduct & Project Management

Install Code to PRD

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill code-to-prd -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alirezarezvani/claude-skills code-to-prd --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/product-team/code-to-prd/skills/code-to-prd .claude/skills/code-to-prd && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-to-prd
GitHub stars
28k
Used in
1 other repo
Token cost
~4.9k tokens
SKILL.md length
1,554 words
Files
10 (incl. scripts, references, assets)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

Reverse-engineers a frontend, backend or fullstack codebase into a product requirements document with per-page docs, an enum dictionary and an API inventory.

  • Works in 8 steps: Project Global Scan → Page-by-Page Deep Analysis → Generate Documentation → …
  • Documenting an existing app that has no written requirements
  • SKILL.md covers Name, Description, Features and Usage, plus 8 more sections
  • Runs Python scripts from its folder; calls python3

What it does

The skill reads an existing codebase and writes a PRD in language product managers can follow, detailed enough for engineers or other agents to rebuild every page and endpoint. It works in three phases: a global scan, page-by-page analysis, then generation of the structured documents.

Two bundled scripts help: codebase_analyzer.py scans a project into an analysis.json file, and prd_scaffolder.py turns that into a prd/ directory skeleton. It recognizes React, Vue, Angular, Svelte, Next.js, Nuxt, SvelteKit and Remix on the frontend, and NestJS, Express, Django, Django REST Framework, FastAPI and Flask on the backend. It separates real API calls from mock data, lists every enum, status code and constant, and extracts models from Django, NestJS entities and Pydantic schemas.

Sample outputs for an enum dictionary, a user list page and a PRD readme come with it, along with a framework-patterns reference and a PRD quality checklist covering completeness, accuracy and readability.

When your agent uses it

  • Documenting an existing app that has no written requirements
  • Producing a functional inventory of pages, fields and interactions
  • Listing API endpoints and model schemas from backend routes
  • Writing a spec detailed enough to rebuild a legacy application

Example prompts

  • “Generate a PRD from the ./src folder of this React app.”
  • “Run code-to-prd on ./myproject and document every Django endpoint and model.”
  • “Create a functional inventory of the pages and API routes in this Next.js project.”

Requirements

  • Python 3 to run the bundled analyzer and scaffolder scripts

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Project Global Scan
  2. Page-by-Page Deep Analysis
  3. Generate Documentation
  4. Business Language First
  5. Don't Miss Hidden Logic
  6. Exhaustively List Enums
  7. Mark Uncertainty — Don't Guess
  8. Keep Page Files Self-Contained

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code to PRD loads about 4.9k tokens when it runs, and up to ~7.6k if it reads all its reference files. Until then it costs about 196 tokens; SKILL.md has 1,554 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~196
When it runs · the whole SKILL.md, loaded when a task matches
~4.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,554 words, ~4,879 tokens.

Download SKILL.mdSave it as .claude/skills/code-to-prd/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
code-to-prd
description
Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Use when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document page logic, analyze page fields and interactions, create a functional inventory, write requirements from an existing codebase, document API endpoints, or analyze backend routes.
license
MIT
metadata.updated
2026-03-17
metadata.tier
STANDARD
metadata.category
product
metadata.dependencies
none
metadata.author
Alireza Rezvani
metadata.version
2.1.2

Name

Code → PRD

Description

Reverse-engineer any frontend, backend, or fullstack codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, models, APIs, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint.

Code → PRD: Reverse-Engineer Any Codebase into Product Requirements

Features

  • 3-phase workflow: global scan → page-by-page analysis → structured document generation
  • Frontend support: React, Vue, Angular, Svelte, Next.js (App + Pages Router), Nuxt, SvelteKit, Remix
  • Backend support: NestJS, Express, Django, Django REST Framework, FastAPI, Flask
  • Fullstack support: Combined frontend + backend analysis with unified PRD output
  • Mock detection: Automatically distinguishes real API integrations from mock/fixture data
  • Enum extraction: Exhaustively lists all status codes, type mappings, and constants
  • Model extraction: Parses Django models, NestJS entities, Pydantic schemas
  • Automation scripts: codebase_analyzer.py for scanning, prd_scaffolder.py for directory generation
  • Quality checklist: Validation checklist for completeness, accuracy, readability

Usage

bash
# Analyze a project and generate PRD skeleton
python3 scripts/codebase_analyzer.py /path/to/project -o analysis.json
python3 scripts/prd_scaffolder.py analysis.json -o prd/ -n "My App"

# Or use the slash command
/code-to-prd /path/to/project

Examples

Frontend (React)
bash
/code-to-prd ./src
# → Scans components, routes, API calls, state management
# → Generates prd/ with per-page docs, enum dictionary, API inventory
Backend (Django)
bash
/code-to-prd ./myproject
# → Detects Django via manage.py, scans urls.py, views.py, models.py
# → Documents endpoints, model schemas, admin config, permissions
Fullstack (Next.js)
bash
/code-to-prd .
# → Analyzes both app/ pages and api/ routes
# → Generates unified PRD covering UI pages and API endpoints

Role

You are a senior product analyst and technical architect. Your job is to read a frontend codebase, understand every page's business purpose, and produce a complete PRD in product-manager-friendly language.

Dual Audience
  1. Product managers / business stakeholders — need to understand what the system does, not how
  2. Engineers / AI agents — need enough detail to fully reconstruct every page's fields, interactions, and relationships

Your document must describe functionality in non-technical language while omitting zero business details.

Supported Stacks
StackFrameworks
FrontendReact, Vue, Angular, Svelte, Next.js (App/Pages Router), Nuxt, SvelteKit, Remix, Astro
BackendNestJS, Express, Fastify, Django, Django REST Framework, FastAPI, Flask
FullstackNext.js (API routes + pages), Nuxt (server/ + pages/), Django (views + templates)

For backend-only projects, the "page" concept maps to API resource groups or admin views. The same 3-phase workflow applies — routes become endpoints, components become controllers/views, and interactions become request/response flows.


Workflow

Phase 1 — Project Global Scan

Build global context before diving into pages.

1. Identify Project Structure

Scan the root directory and understand organization:

Frontend directories:
- Pages/routes (pages/, views/, routes/, app/, src/pages/)
- Components (components/, modules/)
- Route config (router.ts, routes.ts, App.tsx route definitions)
- API/service layer (services/, api/, requests/)
- State management (store/, models/, context/)
- i18n files (locales/, i18n/) — field display names often live here

Backend directories (NestJS):
- Modules (src/modules/, src/*.module.ts)
- Controllers (*.controller.ts) — route handlers
- Services (*.service.ts) — business logic
- DTOs (dto/, *.dto.ts) — request/response shapes
- Entities (entities/, *.entity.ts) — database models
- Guards/pipes/interceptors — auth, validation, transformation

Backend directories (Django):
- Apps (*/apps.py, */views.py, */models.py, */urls.py)
- URL config (urls.py, */urls.py)
- Views (views.py, viewsets.py) — route handlers
- Models (models.py) — database schema
- Serializers (serializers.py) — request/response shapes
- Forms (forms.py) — validation and field definitions
- Templates (templates/) — server-rendered pages
- Admin (admin.py) — admin panel configuration

Identify framework from package.json (Node.js frameworks) or project files (manage.py for Django, requirements.txt/pyproject.toml for Python). Routing, component patterns, and state management differ significantly across frameworks — identification enables accurate parsing.

2. Build Route & Page Inventory

Extract all pages from route config into a complete page inventory:

FieldDescription
Route pathe.g. /user/list, /order/:id
Page titleFrom route config, breadcrumbs, or page component
Module / menu levelWhere it sits in navigation
Component file pathSource file(s) implementing this page

For file-system routing (Next.js, Nuxt), infer from directory structure.

For backend projects, the page inventory becomes an endpoint/resource inventory:

FieldDescription
Endpoint pathe.g. /api/users, /api/orders/:id
HTTP methodGET, POST, PUT, DELETE, PATCH
Controller/viewSource file handling this route
Module/appWhich NestJS module or Django app owns it
Auth requiredWhether authentication/permissions are needed

For NestJS: extract from @Controller + @Get/@Post/@Put/@Delete decorators. For Django: extract from urls.py → urlpatterns and viewsets.py → router registrations.

3. Map Global Context

Before analyzing individual pages, capture:

  • Global state — user info, permissions, feature flags, config
  • Shared components — layout, nav, auth guards, error boundaries
  • Enums & constants — status codes, type mappings, role definitions
  • API base config — base URL, interceptors, auth headers, error handling
  • Database models (backend) — entity relationships, field types, constraints
  • Middleware (backend) — auth middleware, rate limiting, logging, CORS
  • DTOs/Serializers (backend) — request validation shapes, response formats

These will be referenced throughout page/endpoint analysis.


Phase 2 — Page-by-Page Deep Analysis

Analyze every page in the inventory. Each page produces its own Markdown file.

Analysis Dimensions

For each page, answer:

A. Page Overview
  • What does this page do? (one sentence)
  • Where does it fit in the system?
  • What scenario brings a user here?
B. Layout & Regions
  • Major regions: search area, table, detail panel, action bar, tabs, etc.
  • Spatial arrangement: top/bottom, left/right, nested
C. Field Inventory (core — be exhaustive)

For form pages, list every field:

Field NameTypeRequiredDefaultValidationBusiness Description
UsernameText inputYes—Max 20 charsSystem login account

For table/list pages, list:

  • Search/filter fields (type, required, enum options)
  • Table columns (name, format, sortable, filterable)
  • Row action buttons (what each one does)

Field name extraction priority:

  1. Hardcoded display text in code
  2. i18n translation values
  3. Component placeholder / label / title props
  4. Variable names (last resort — provide reasonable display name)
D. Interaction Logic

Describe as "user action → system response":

[Action]     User clicks "Create"
[Response]   Modal opens with form fields: ...
[Validation] Name required, phone format check
[API]        POST /api/user/create with form data
[Success]    Toast "Created successfully", close modal, refresh list
[Failure]    Show API error message

Cover all interaction types:

  • Page load / initialization (default queries, preloaded data)
  • Search / filter / reset
  • CRUD operations (create, read, update, delete)
  • Table: pagination, sorting, row selection, bulk actions
  • Form submission & validation
  • Status transitions (e.g. approval flows: pending → approved → rejected)
  • Import / export
  • Field interdependencies (selecting value A changes options in field B)
  • Permission controls (buttons/fields visible only to certain roles)
  • Polling / auto-refresh / real-time updates
E. API Dependencies

Case 1: API is integrated (real HTTP calls in code)

API NameMethodPathTriggerKey ParamsNotes
Get usersGET/api/user/listLoad, searchpage, size, keywordPaginated

Case 2: API not integrated (mock/hardcoded data)

When the page uses mock data, hardcoded fixtures, setTimeout simulations, or Promise.resolve() stubs — the API isn't real yet. Reverse-engineer the required API spec from page functionality and data shape.

For each needed API, document:

  • Method, suggested path, trigger
  • Input params (name, type, required, description)
  • Output fields (name, type, description)
  • Core business logic description

Detection signals:

  • setTimeout / Promise.resolve() returning data → mock
  • Data defined in component or *.mock.* files → mock
  • Real HTTP calls (axios, fetch, service layer) with real paths → integrated
  • __mocks__ directory → mock
F. Page Relationships
  • Inbound: Which pages link here? What parameters do they pass?
  • Outbound: Where can users navigate from here? What parameters?
  • Data coupling: Which pages share data or trigger refreshes in each other?

Phase 3 — Generate Documentation
Output Structure

Create prd/ in project root (or user-specified directory):

prd/
├── README.md                     # System overview
├── pages/
│   ├── 01-user-mgmt-list.md      # One file per page
│   ├── 02-user-mgmt-detail.md
│   ├── 03-order-mgmt-list.md
│   └── ...
└── appendix/
    ├── enum-dictionary.md         # All enums, status codes, type mappings
    ├── page-relationships.md      # Navigation map between pages
    └── api-inventory.md           # Complete API reference
README.md Template
markdown
# [System Name] — Product Requirements Document

## System Overview
[2-3 paragraphs: what the system does, business context, primary users]

## Module Overview

| Module | Pages | Core Functionality |
|--------|-------|--------------------|
| User Management | User list, User detail, Role mgmt | CRUD users, assign roles and permissions |

## Page Inventory

| # | Page Name | Route | Module | Doc Link |
|---|-----------|-------|--------|----------|
| 1 | User List | /user/list | User Mgmt | [→](./pages/01-user-mgmt-list.md) |

## Global Notes

### Permission Model
[Summarize auth/role system if present in code]

### Common Interaction Patterns
[Global rules: all deletes require confirmation, lists default to created_at desc, etc.]
Per-Page Document Template
markdown
# [Page Name]

> **Route:** `/xxx/xxx`
> **Module:** [Module name]
> **Generated:** [Date]

## Overview
[2-3 sentences: core function and use case]

## Layout
[Region breakdown — text description or ASCII diagram]

## Fields

### [Region: e.g. "Search Filters"]
| Field | Type | Required | Options / Enum | Default | Notes |
|-------|------|----------|---------------|---------|-------|

### [Region: e.g. "Data Table"]
| Column | Format | Sortable | Filterable | Notes |
|--------|--------|----------|-----------|-------|

### [Region: e.g. "Actions"]
| Button | Visibility Condition | Behavior |
|--------|---------------------|----------|

## Interactions

### Page Load
[What happens on mount]

### [Scenario: e.g. "Search"]
- **Trigger:** [User action]
- **Behavior:** [System response]
- **Special rules:** [If any]

### [Scenario: e.g. "Create"]
- **Trigger:** ...
- **Modal/drawer content:** [Fields and logic inside]
- **Validation:** ...
- **On success:** ...

## API Dependencies

| API | Method | Path | Trigger | Notes |
|-----|--------|------|---------|-------|
| ... | ... | ... | ... | ... |

## Page Relationships
- **From:** [Source pages + params]
- **To:** [Target pages + params]
- **Data coupling:** [Cross-page refresh triggers]

## Business Rules
[Anything that doesn't fit above]

Key Principles

Show full SKILL.md (622 more words)Show less
1. Business Language First

Don't write "calls useState to manage loading state." Write "search button shows a spinner to prevent duplicate submissions."

Don't write "useEffect fetches on mount." Write "page automatically loads the first page of results on open."

Include technical details only when they directly affect product behavior: API paths (engineers need them), validation rules (affect UX), permission conditions (affect visibility).

2. Don't Miss Hidden Logic

Code contains logic PMs may not realize exists:

  • Field interdependencies (type A shows field X; type B shows field Y)
  • Conditional button visibility
  • Data formatting (currency with 2 decimals, date formats, status label mappings)
  • Default sort order and page size
  • Debounce/throttle effects on user input
  • Polling / auto-refresh intervals
3. Exhaustively List Enums

When code defines enums (status codes, type codes, role types), list every value and its meaning. These are often scattered across constants files, component valueEnum configs, or API response mappers.

4. Mark Uncertainty — Don't Guess

If a field or logic's business meaning can't be determined from code (e.g. abbreviated variable names, overly complex conditionals), mark it [TBC] and explain what you observed and why you're uncertain. Never fabricate business meaning.

5. Keep Page Files Self-Contained

Each page's Markdown should be standalone — reading just that file gives complete understanding. Use relative links when referencing other pages or appendix entries.


Page Type Strategies

Frontend Pages
Page TypeFocus Areas
List / TableSearch conditions, columns, row actions, pagination, bulk ops
Form / Create-EditEvery field, validation, interdependencies, post-submit behavior
Detail / ViewDisplayed info, tab/section organization, available actions
Modal / DrawerDescribe as part of triggering page — not a separate file. But fully document content
DashboardData cards, charts, metrics meaning, filter dimensions, refresh frequency
Backend Endpoints (NestJS / Django / Express)
Endpoint TypeFocus Areas
CRUD resourceAll fields (from DTO/serializer), validation rules, permissions, pagination, filtering, sorting
Auth endpointsLogin/register flow, token format, refresh logic, password reset, OAuth providers
File uploadAccepted types, size limits, storage destination, processing pipeline
Webhook / eventTrigger conditions, payload shape, retry policy, idempotency
Background jobTrigger, schedule, input/output, failure handling, monitoring
Admin views (Django)Registered models, list_display, search_fields, filters, inline models, custom actions

Execution Pacing

Large projects (>15 pages): Work in batches of 3-5 pages per module. Complete system overview + page inventory first. Output each batch for user review before proceeding.

Small projects (≤15 pages): Complete all analysis in one pass.


Common Pitfalls

PitfallFix
Using component names as page namesUserManagementTable → "User Management List"
Skipping modals and drawersThey contain critical business logic — document fully
Missing i18n field namesCheck translation files, not just component JSX
Ignoring dynamic route params/order/:id = page requires an order ID to load
Forgetting permission controlsDocument which roles see which buttons/pages
Assuming all APIs are realCheck for mock data patterns before documenting endpoints
Skipping Django admin customizationadmin.py often contains critical business rules (list filters, custom actions, inlines)
Missing NestJS guards/pipes@UseGuards, @UsePipes contain auth and validation logic that affects behavior
Ignoring database constraintsModel field constraints (unique, max_length, choices) are validation rules for the PRD
Overlooking middlewareAuth middleware, rate limiters, and CORS config define system-wide behavior

Tooling

Scripts
ScriptPurposeUsage
scripts/codebase_analyzer.pyScan codebase → extract routes, APIs, models, enums, structurepython3 codebase_analyzer.py /path/to/project
scripts/prd_scaffolder.pyGenerate PRD directory skeleton from analysis JSONpython3 prd_scaffolder.py analysis.json

Recommended workflow:

bash
# 1. Analyze the project (JSON output — works for frontend, backend, or fullstack)
python3 scripts/codebase_analyzer.py /path/to/project -o analysis.json

# 2. Review the analysis (markdown summary)
python3 scripts/codebase_analyzer.py /path/to/project -f markdown

# 3. Scaffold the PRD directory with stubs
python3 scripts/prd_scaffolder.py analysis.json -o prd/ -n "My App"

# 4. Fill in TODO sections page-by-page using the SKILL.md workflow

Both scripts are stdlib-only — no pip install needed.

References
FileContents
references/prd-quality-checklist.mdValidation checklist for completeness, accuracy, readability
references/framework-patterns.mdFramework-specific patterns for routes, state, APIs, forms, permissions

Attribution

This skill was inspired by code-to-prd by @lihanglogan, who proposed the original concept and methodology in PR #368. The core three-phase workflow (global scan → page-by-page analysis → structured document generation) originated from that work. This version was rebuilt from scratch in English with added tooling (analysis scripts, scaffolder, framework reference, quality checklist).

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts, references, assets) in product-team/code-to-prd/skills/code-to-prd of alirezarezvani/claude-skills.

  • SKILL.md
  • assets/sample-analysis.json
  • expected_outputs/sample-enum-dictionary.md
  • expected_outputs/sample-page-user-list.md
  • expected_outputs/sample-prd-readme.md
  • references/framework-patterns.md
  • references/prd-quality-checklist.md
  • scripts/.gitignore
  • scripts/codebase_analyzer.py
  • scripts/prd_scaffolder.py

Open the folder on GitHubat commit 19392f7

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in alirezarezvani/claude-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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    28k GitHub starsUsed in 1 repo~2.1k tokens
    Auto-check passed
  • Customer Success Manager

    alirezarezvani/claude-skills

    Scores customer health, churn risk and expansion potential from a JSON export of account data, using three Python scripts that need no extra libraries.

    28k GitHub starsUsed in 1 repo~2.3k tokens
    Auto-check passed

Questions about Code to PRD

What does Code to PRD do?

Reverse-engineers a frontend, backend or fullstack codebase into a product requirements document with per-page docs, an enum dictionary and an API inventory. The skill reads an existing codebase and writes a PRD in language product managers can follow, detailed enough for engineers or other agents to rebuild every page and endpoint. It works in three phases: a global scan, page-by-page analysis, then generation of the structured documents.

When should I use Code to PRD?

Code to PRD fits situations like: documenting an existing app that has no written requirements; producing a functional inventory of pages, fields and interactions; listing API endpoints and model schemas from backend routes; writing a spec detailed enough to rebuild a legacy application.

How do I install Code to PRD in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill code-to-prd -a claude-code`. Or copy the skill folder (product-team/code-to-prd/skills/code-to-prd in alirezarezvani/claude-skills) into .claude/skills/code-to-prd in your project. Claude Code loads it when a task matches its description.

How do I install Code to PRD in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill code-to-prd -a codex`. Or copy the skill folder (product-team/code-to-prd/skills/code-to-prd in alirezarezvani/claude-skills) into .agents/skills/code-to-prd in your project. Codex loads it when a task matches its description.

Can I use Code to PRD in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill code-to-prd -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-to-prd, .gemini/skills/code-to-prd, .github/skills/code-to-prd and .opencode/skills/code-to-prd in your project.

What does Code to PRD need to run?

Going by SKILL.md and its folder, Code to PRD needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3 to run the bundled analyzer and scaffolder scripts.

Does Code to PRD access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Code to PRD safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Code to PRD use?

Code to PRD is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code to PRD use?

About 4.9k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.7k tokens, read only when the agent opens those files.

What are the alternatives to Code to PRD?

Skills that share tags, products or a category with Code to PRD: Senior Fullstack (borghei/Claude-Skills, 874 stars), Typescript Docs (giuseppe-trisciuoglio/developer-kit, 355 stars), Documentation Lookup (KaimingWan/oh-my-kiro, 107 stars) and Htmx (ericrisco/rsc-harness, 156 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code to PRD?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,788 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.