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    README Rescue Architect for AI Coding Agents

    README Rescue Architect for AI Coding Agents

    Transforms undocumented repositories into professional README files, setup guides, command maps, architecture notes, environment references, testing docs, and AI agent handoff files.

    Updated May 2026
    Security scanned
    One-time purchase
    Compatible with ChatGPT Custom GPTs

    $9.99

    · or 50 credits

    One-time purchase

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Generate a professional README package for inherited legacy codebases.
    • Create an AI_AGENT_HANDOFF.md to prevent AI agents from breaking risky code.
    • file_write, file_read, terminal automation included
    • Ready for Compatible with ChatGPT Custom GPTs
    • Instant install

    Sample Output

    A real example of what this skill produces.

    === README RESCUE PLAN ===

    Project/repository: Node/React project with no useful documentation

    Documentation goal: Create a professional documentation package that helps developers and future AI coding agents install, run, understand, test, troubleshoot, and safely modify the project.

    Repository type: JavaScript/React project, exact architecture to be confirmed by inspection

    Confirmed facts:

    • The project uses Node.
    • The project uses React.
    • The repository has package.json.
    • The repository has source folders.
    • Environment variables exist.
    • Tests are currently unknown.
    • Deployment is unclear.
    • Current documentation is not useful.

    Assumptions:

    • package.json contains install, dev, build, or test scripts.
    • source folders contain the main React application.
    • environment variables may be required for local setup.
    • deployment clues may exist in config files, scripts, CI files, or hosting config.

    Unknowns to clarify:

    • package manager
    • React framework or build tool
    • development command
    • build command
    • test framework
    • deployment platform
    • environment variable names
    • application entry point
    • routing structure
    • API/backend presence

    Documentation gap audit: Project purpose: Missing

    Setup: Missing

    Commands: Unknown until package.json is inspected

    Architecture: Missing

    Testing: Unknown

    Deployment: Unknown

    Environment variables: Known to exist but undocumented

    Troubleshooting: Missing

    AI agent readiness: Weak. A future AI coding agent would not know the repository purpose, commands, structure, risks, or verification steps.

    Recommended documentation package:

    1. README.md
    2. SETUP.md
    3. COMMANDS.md
    4. ARCHITECTURE.md
    5. ENVIRONMENT.md
    6. TESTING.md
    7. TROUBLESHOOTING.md
    8. AI_AGENT_HANDOFF.md

    README.md outline:

    • Project name
    • Short description
    • Status
    • Tech stack
    • Key features
    • Quick start
    • Documentation links
    • Common commands
    • Project structure
    • Testing
    • Build
    • Deployment status
    • Known limitations

    SETUP.md outline:

    • Prerequisites
    • Package manager
    • Installation command
    • Environment setup
    • Local development command
    • Expected local URL
    • Setup verification checklist
    • Common setup errors

    COMMANDS.md outline:

    • dependency installation command
    • development command
    • build command
    • test command if available
    • lint command if available
    • preview command if available
    • command warnings and expected results

    ARCHITECTURE.md outline:

    • high-level system overview
    • source folder structure
    • entry point
    • routing
    • components
    • state management if present
    • API/data flow if present
    • configuration
    • risky areas

    TESTING.md outline:

    • test framework if present
    • test command if present
    • test folders
    • how to run tests
    • recommended first tests if no tests exist
    • manual QA checklist

    TROUBLESHOOTING.md outline:

    • install failures
    • missing environment variables
    • port conflicts
    • build failures
    • test failures
    • API connection errors
    • unclear deployment failures

    AI_AGENT_HANDOFF.md outline:

    • repository purpose
    • tech stack
    • important folders
    • common commands
    • environment variable safety notes
    • architecture overview
    • risky areas
    • do not change casually
    • verification checklist
    • safe prompt template for future AI agents

    Documentation recovery prompt: Inspect this Node/React repository and create a professional documentation package. Before writing, inspect package.json, lockfiles, README files, source folders, routes, components, configuration files, test setup, build setup, deployment clues, docs folders, and environment examples. Identify environment variable names only and never expose secret values. Document only confirmed commands and clearly label assumptions. Create README.md, SETUP.md, COMMANDS.md, ARCHITECTURE.md, ENVIRONMENT.md, TESTING.md, TROUBLESHOOTING.md, and AI_AGENT_HANDOFF.md. Do not change application code. Return files inspected, documents created, assumptions made, gaps remaining, and verification checklist.

    Verification checklist:

    • README explains what the project does.
    • Setup guide allows a developer to run the project.
    • Commands are documented accurately from package.json or clearly marked as unconfirmed.
    • Environment variables are documented by name only.
    • Testing status is clear.
    • Architecture overview explains where to start.
    • Troubleshooting covers common setup failures.
    • AI_AGENT_HANDOFF.md helps future AI agents work safely.
    • No secrets or private credentials are included.

    Risks and safety notes: Because deployment and tests are unclear, documentation should not claim verified deployment or test coverage until commands are inspected and executed. Environment variable values must never be exposed.

    About This Skill

    README Rescue Architect helps AI coding agents, developers, founders, freelancers, students, maintainers, agencies, and software teams turn confusing or undocumented repositories into clear, professional documentation systems. It creates README rescue plans, README.md drafts, setup guides, command maps, architecture overviews, environment variable references by name only, testing guides, deployment notes, troubleshooting sections, known-risk documents, onboarding docs, and AI_AGENT_HANDOFF.md files for future coding agents. The skill is ideal for documenting inherited codebases, preparing open-source repositories, improving developer onboarding, making projects easier to run, and helping AI coding agents understand a repository before editing it.

    📖 Learn more: Best DevOps & Deployment Skills for Claude Code →

    Use Cases

    • Generate a professional README package for inherited legacy codebases.
    • Create an AI_AGENT_HANDOFF.md to prevent AI agents from breaking risky code.
    • Audit repository documentation gaps and generate high-priority fix tasks.
    • Produce safe environment variable references without exposing private secrets.
    • Build command maps for run, test, build, and deploy workflows from source.

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    Security Scanned

    Passed automated security review

    Permissions

    Write Files
    Read Files
    Terminal / Shell

    Allowed Hosts

    https://promptbase.com/profile/shandra?via=mhq19

    File Scopes

    *.md
    *.txt
    *.json
    *.yaml
    *.yml
    *.toml
    README.md
    package.json
    composer.json
    requirements.txt
    pyproject.toml
    Dockerfile
    docker-compose.*
    Makefile
    src/**
    app/**
    server/**
    api/**
    routes/**
    components/**
    services/**
    scripts/**
    tests/**
    docs/**
    config/**
    .github/**

    This skill uses file access to read user-provided README files, repository notes, documentation folders, package manifests, scripts, configuration examples, code snippets, test folders, deployment clues, Docker files, CI files, and environment examples. It uses write access to create structured Markdown/text documentation such as README.md, setup guides, command maps, architecture notes, environment variable references, testing guides, deployment notes, troubleshooting guides, known-risk documents, AI agent handoff files, documentation audits, and SKILL.md files. Terminal access is optional and should only be enabled when the agent is expected to verify commands, inspect scripts, or run tests. Environment variable values and secrets should never be exposed.

    Compatible with ChatGPT Custom GPTs, ChatGPT Agents, Cursor, Claude Code, Codex CLI, OpenCode, Replit, GitHub Copilot-style workflows, and other AI coding assistants that support structured Markdown instruction files such as SKILL.md. It can also be used manually in any AI chat by pasting the instructions.

    Frequently Asked Questions

    $10