skills/utility-skills/project-handoff-ingestion/SKILL.md
Systematic ingestion and verification of handoff projects from other development environments (Cursor, VS Code, etc.). Use when receiving project handoffs, verifying deployment status, analyzing codebases for the first time, or creating comprehensive system documentation for inherited projects.
npx skillsauth add abcnuts/manus-skills project-handoff-ingestionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Systematic process for ingesting projects handed off from other development environments, verifying all components, and creating comprehensive deployment documentation.
Use this skill when you receive a project handoff and need to:
Read and analyze all provided handoff documentation:
Create an initial assessment document tracking:
Systematically verify access to each mentioned service:
Live Services (HTTP/HTTPS)
Databases
Source Code Repositories
Deployment Platforms
Compare documentation claims against actual findings:
Create a discrepancy table: | Component | Documentation Claims | Actual Finding | Impact | |-----------|---------------------|----------------|--------| | Example | "95% complete" | "60% complete, payment system not deployed" | High |
Common discrepancies to check:
Once repository access is obtained:
Examine Project Structure
Analyze Implementation
Check Dependencies
Test all documented API endpoints:
# Health check
curl https://api-url/health
# POST endpoints
curl -X POST https://api-url/endpoint \
-H "Content-Type: application/json" \
-d '{"test": "data"}'
Document results:
If using Supabase MCP:
# List all tables
manus-mcp-cli tool call execute_sql --server supabase \
--input '{"project_id":"PROJECT_ID","query":"SELECT table_name FROM information_schema.tables WHERE table_schema = '\''public'\'';"}'
# Check table schema
manus-mcp-cli tool call execute_sql --server supabase \
--input '{"project_id":"PROJECT_ID","query":"SELECT * FROM table_name LIMIT 5;"}'
Verify:
Maintain a detailed execution log throughout the process:
# Project Ingestion Log
## Phase 1: Documentation Analysis ✅
- Read handoff document
- Identified 5 services
- Found 12 environment variables
## Phase 2: Service Verification ⚠️
- API: ✅ Online (response time: 450ms)
- Database: ✅ Accessible via MCP
- Repository: ❌ Access denied
- Frontend: ✅ Deployed and responsive
## Phase 3: Discrepancies Found
1. Payment endpoints documented but not deployed
2. Stripe keys claimed missing but actually configured
...
Create final deliverables:
System Health Report
Deployment Guide
When repository access is denied:
gh auth status to verify GitHub CLI is authenticatedWhen exploring unknown databases:
information_schema for all tables*config*, *secret*, *setting*project_registry or similar metadata tablesDon't assume documentation is accurate: Always verify claims against actual system state.
Don't skip endpoint testing: Even if documentation says endpoints exist, test them.
Don't forget to log discrepancies: Track every difference between docs and reality.
Don't overlook environment variables: Check deployment platforms directly, not just documentation.
Don't proceed without repository access: Code analysis is critical for understanding implementation.
The ingestion is complete when you can answer:
tools
Generate comprehensive demonstrations showing how to access projects and work across different environments (Manus terminals, personal computers, team collaboration). Use when users ask "how do I access this from another terminal/computer", "how do I share this with my team", "how do I get this on my Mac", or need clarification on Manus persistence vs GitHub usage.
development
Use when you have a spec or requirements for a multi-step task, before touching code
data-ai
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
development
Use when implementing any feature or bugfix, before writing implementation code