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- README Rescue Architect for AI Coding Agents
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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.
$9.99
README Rescue Architect for AI Coding Agents
Example session with this skill installed
Create a README rescue plan and AI coding agent documentation prompt for a Node/React project with no useful documentation. The repository has a package.json, source folders, some environment variables, unknown tests, and unclear deployment. I want README.md, SETUP.md, COMMANDS.md, ARCHITECTURE.md, TESTING.md, TROUBLESHOOTING.md, and AI_AGENT_HANDOFF.md. Do not expose secret values.
- Read your context and instructions
- Compiled the readme rescue architect
- Generated the document
=== 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
- README.md
- SETUP.md
- COMMANDS.md
- ARCHITECTURE.md
- ENVIRONMENT.md
- TESTING.md
- TROUBLESHOOTING.md
- 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.
readme-rescue-architect-for-ai-coding-ag.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
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.
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- 1
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- 2
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- 3
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