Project Auto Builder

Project Auto Builder

Prerequisites & Dependencies

• Access to ./skills/ flat directory containing all skill .md files
• Access to ./registry.json at repository root for skill indexing and metadata
• Python 3.10+ runtime for orchestration logic and JSON processing
• jq for JSON parsing and skill metadata extraction
• inquirer or equivalent for interactive workspace stack detection (optional, defaults to automated detection)
• Node.js/Python version managers for runtime detection (nvm, pyenv, etc.)

Execution Steps

1. Registry Inspection

• Read ./registry.json at the repository root
• Parse the full skill catalog: extract each skill's id, name, category, tags, and description
• Build an in-memory index of all available skills, grouped by category and tagged for quick lookup
• Validate registry JSON schema integrity — if malformed, halt and report: "Registry corrupted: cannot proceed with auto-build"
• Output: registry-index.json — a condensed map of {id: {name, category, tags, description}}

2. Workspace Analysis

• Scan the project directory for language/runtime markers:
  • Node.js: presence of package.json, node_modules, tsconfig.json
  • Python: presence of requirements.txt, pyproject.toml, setup.py, .python-version
  • Docker: presence of Dockerfile, docker-compose.yml, .dockerignore
  • Mixed stacks: detect multiple language runtimes in parallel
• Determine the primary project type and secondary language/runtime artifacts
• Capture available tooling versions (node version, python version, docker availability)
• Output: workspace-profile.json — {primary_stack: "node|python|docker|mixed", versions: {...}, markers: [...]}

3. Dynamic Matching

• Cross-reference the workspace-profile.json against the registry-index.json
• Scoring algorithm: for each skill, compute a match score based on:
  • Tag overlap between skill tags and detected stack markers
  • Category relevance (e.g., backend skills for server-side stacks, data-science for Python data workloads)
  • Explicit stack mentions in skill description
• Sort skills by match score (descending) to produce an optimal execution order
• Allow user overrides: permit the user to promote/demote specific skills via --prioritize / --demote CLI flags
• Output: skill-order.json — ordered list of skill IDs with match scores: [{id, score, reason}]

4. Execution Report

• Execute skills in the order determined by skill-order.json
• For each skill:
  • Invoke the skill's primary functionality (or a representative summary if the skill has no executable main function)
  • Capture exit code, stdout, stderr, and generated artifacts
  • Track pass/fail status per skill
• After all skills execute, generate a comprehensive readiness-summary.md report including:
  • Which skills were selected and their match scores
  • Execution results per skill (pass/fail, key outputs)
  • Overall project readiness status
  • Recommendations for next steps (e.g., "run verify-orchestrator", "missing: Dockerfile")
• Output: readiness-summary.md — human-readable markdown report

5. Fallback Behavior

If no skills match the detected workspace stack:

• List all skills with their match scores (even low ones)
• Prompt the user: "No high-match skills found. Proceed with lowest-match skill or manual selection?"
• If user chooses manual selection, present the ranked list and allow ID-based selection
• If user chooses lowest-match, execute the top-1 ranked skill with reduced expectations flag

CLI Interface

project-auto-builder [--list] [--prioritize <comma-separated-ids>] [--demote <comma-separated-ids>]
  --list                 List all available skills from registry
  --prioritize           Promote specific skill IDs to top of execution order
  --demote               Demote specific skill IDs to bottom of execution order

Example Workflow

# Auto-build for a Node.js project
project-auto-builder

# Internal execution flow:
1. Read ./registry.json → index 40 skills
2. Scan workspace → detect Node.js stack, v18.17.0
3. Match skills → rank by tag overlap: ["rate-limiter-middleware"(92%), "websocket-realtime-handler"(88%), ...]
4. Execute in order → capture artifacts
5. Generate readiness-summary.md

# Output sample (readiness-summary.md)
# Project Auto Builder Report
## Stack Detected: Node.js v18.17.0
## Selected Skills (3 of 5 top-matched):
1. **rate-limiter-middleware** (match: 92%) — ✅ Executed, middleware scaffold generated at ./skills/output/rate-limiter-middleware/
2. **websocket-realtime-handler** (match: 88%) — ✅ Executed, WS handler skeleton at ./skills/output/websocket-realtime-handler/
3. **cli-tool-scaffolder** (match: 81%) — ✅ Executed, CLI tool at ./skills/output/cli-tool-scaffolder/
## Overall Readiness: 85% — All top-matched skills executed successfully.
## Recommendations: Consider running verify-orchestrator to validate integration.