onboard
Scannednpx machina-cli add skill parcadei/Continuous-Claude-v3/onboard --openclawOnboard - Project Discovery & Ledger Creation
Analyze a brownfield codebase and create an initial continuity ledger.
When to Use
- First time working in an existing project
- User says "onboard", "analyze this project", "get familiar with codebase"
How to Use
Spawn the onboard agent:
Use the Task tool with subagent_type: "onboard" and this prompt:
Onboard me to this project at $CLAUDE_PROJECT_DIR.
1. Create required directories if they don't exist:
mkdir -p thoughts/shared/handoffs/<project-name> .claude
2. Explore the codebase using available tools:
- Try: tldr tree . && tldr structure .
- Fallback: find . -type f -name "*.py" -o -name "*.ts" -o -name "*.js" | head -50
3. Detect tech stack (look for package.json, requirements.txt, Cargo.toml, go.mod, etc.)
4. Ask the user about their goals using AskUserQuestion
5. Create a YAML handoff at thoughts/shared/handoffs/<project-name>/onboard-<date>.yaml:
---
date: <ISO date>
type: onboard
status: active
---
goal: <user's stated goal>
now: Start working on <first priority>
tech_stack: [list of detected technologies]
key_files:
- path: <important file>
purpose: <what it does>
architecture: <brief description>
next:
- <suggested first action>
Why an Agent?
The onboard process:
- Requires multiple exploration steps
- Should not pollute main context with codebase dumps
- Returns a clean summary + creates the handoff
Output
- Directories created:
thoughts/shared/handoffs/<project>/,.claude/ - YAML handoff created (loaded automatically on session start)
- User has clear starting context
- Ready to begin work with full project awareness
Notes
- This skill is for BROWNFIELD projects (existing code)
- For greenfield, use
/create_planinstead - Handoff can be updated anytime with
/create_handoff
Source
git clone https://github.com/parcadei/Continuous-Claude-v3/blob/main/.claude/skills/onboard/SKILL.mdView on GitHub Overview
Onboard analyzes a brownfield codebase and creates the initial continuity ledger. It sets up dedicated thoughts folders, inventories the tech stack and key files, and outputs a YAML handoff summarizing goals, current status, and next actions.
How This Skill Works
Spawn the onboard agent, explore the repository (tree/structure) and detect tech stack, then query the user for goals. It writes a YAML handoff at thoughts/shared/handoffs/<project-name>/onboard-<date>.yaml containing date, type, status, goal, now, tech_stack, key_files, architecture, and next actions, while leaving the main context clean.
When to Use It
- First time working in an existing brownfield project
- User asks to onboard, analyze this project, or get familiar with codebase
- You need an initial continuity ledger and a project summary before heavy work
- Preparing teammates with a shareable handoff and project context
- Starting a brownfield project and requiring a structured discovery phase
Quick Start
- Step 1: Spawn the onboard agent with subagent_type: "onboard" and point to the project directory
- Step 2: Run exploration to detect tech stack and collect key files (e.g., tree ., structure ., and common config files)
- Step 3: Answer the user questions, then the agent creates thoughts/shared/handoffs/<project-name>/onboard-<date>.yaml and initializes the project context
Best Practices
- Confirm the project name to generate correct paths: thoughts/shared/handoffs/<project-name> and .claude
- Run exploration steps (tree/structure) and tech stack detection before deep changes
- Ask the user about goals early to populate the 'goal' and 'now' fields accurately
- Create and store the YAML handoff at onboard-<date>.yaml and keep dumps out of main context
- Use the handoff as a living reference; update it with /create_handoff as goals evolve
Example Use Cases
- Onboard a React + Node.js monorepo: tech_stack includes JavaScript, Node.js, React; key_files: package.json, package-lock.json, tsconfig.json; architecture described as a multi-service frontend-backend setup
- Onboard a Python Django app: tech_stack includes Python, Django, PostgreSQL; key_files: requirements.txt, manage.py, settings.py; architecture described as a traditional MVC web app
- Onboard a Go microservice: tech_stack includes Go, Docker; key_files: go.mod, main.go, Dockerfile; architecture described as a set of microservices with API gateway
- Onboard a Rust CLI tool: tech_stack includes Rust, cargo; key_files: Cargo.toml, src/main.rs; architecture described as a single executable with modular crates
- Onboard a large monorepo with multiple services: tech_stack spans JS/TS, Python, and Go; key_files span multiple service folders; architecture described as a polyrepo with service boundaries and shared libs