SKILL.md
Project Bootstrap
Automated setup skill for bootstrapping Claude Code in any project. Detects whether you're in a greenfield or brownfield project, identifies the tech stack, copies relevant skills from your skill library, and creates specialized engineer agents.
Configuration
This skill uses hardcoded paths for personal use:
- Skill Library:
C:\Users\coper\Documents\GitHub\agent-skills\skills
- Unpack Destination:
.claude/skills/ in the current project
Workflow
Phase 1: Project Detection
- Check if
.claude/ exists (indicates brownfield with some setup)
- Check for common project files:
package.json, pyproject.toml, go.mod, Cargo.toml, etc.
- If no project files found → greenfield project
- If project files found → brownfield project
Phase 2: Information Gathering
For Greenfield Projects:
- Search for README.md, specs, or planning documents
- If found, extract project intent from those files
- If not found or unclear, use AskUserQuestion to interview user about:
- What are you building? - Primary language/framework? - Backend, frontend, or full-stack? - Any specific libraries or tools needed?
For Brownfield Projects:
- Spawn Explore sub-agent to analyze codebase (stack, structure, patterns)
- Spawn Explore sub-agent to check existing
.claude/ setup (agents, skills, commands)
- Wait for both reports before proceeding
Phase 3: Skill Selection
- Read
references/skill-categories.md for available skills mapping
- Match project stack to relevant skills using keyword matching
- Always include
best-practices skill if available
- Present selections to user via AskUserQuestion for confirmation
- User can add/remove skills from the selection
Phase 4: Skill Deployment
- Create
.claude/skills/ directory if needed
- Copy selected
.skill files from skill library
- Unpack each skill (extract zip to folder, delete .skill file)
- Verify unpacked structure (SKILL.md exists)
Phase 5: Agent Creation
Automatically create agents without further confirmation (per user preference).
CRITICAL: Agent Prompt Quality
Each agent must have a rich, comprehensive system prompt following the agent creation architect framework. DO NOT create basic or minimal prompts. Each agent prompt should include:
- Expert Persona: A compelling identity with deep domain knowledge
- Core Intent: Clear purpose and success criteria
- Comprehensive Instructions: Methodologies, best practices, edge case handling
- Decision Frameworks: How to approach choices and trade-offs
- Quality Control: Self-verification steps and output expectations
- Workflow Patterns: Step-by-step process for task execution
Agent Types to Create:
Engineer Agents (1-3 based on stack):
- Create stack-specific engineers (e.g.,
typescript-engineer, python-engineer)
- Include best-practices skill reference
- Include relevant library skills
- Use rich prompts from
references/agent-templates.md
Code Quality Agents:
- Create
code-quality agent for the primary language
- Include linting/formatting skills (biome, ruff, etc.)
- Include best-practices skill
- Define clear quality checklist and verification steps
Library-Specific Agents (if applicable):
- Create agents for major frameworks (react, angular, express, etc.)
- Only if corresponding skill was copied
- Keep minimal (don't create agent for every skill)
- Include framework-specific patterns and best practices
See references/agent-templates.md for comprehensive agent creation patterns with rich prompts.
Phase 6: Validation & Summary
- Run
scripts/validate_setup.py to check all skills and agents
- Report any issues found
- Print summary of what was set up:
- Skills copied and unpacked - Agents created - Any issues or warnings
Decision Framework
When to Ask vs. Automate
| Situation |
Action |
| Greenfield with no specs |
Ask about project intent |
| Skill selection |
Always confirm with user |
| Agent creation |
Fully automatic |
| Unclear stack |
Ask for clarification |
| Multiple valid approaches |
Ask for preference |
Stack Detection Keywords
| Keyword |
Skills to Suggest |
typescript, javascript |
typescript-best-practices, biome, vite |
react |
react-19, react-ecosystem skills |
python |
python-best-practices, ruff-dev, pytest |
go |
go-best-practices |
rust |
rust-dev |
angular |
angular skill |
fastapi |
fastapi skill |
express |
express skill |
Scripts
scripts/validate_setup.py
Validates all unpacked skills and agents in .claude/:
- Checks SKILL.md exists in each skill folder
- Validates agent YAML frontmatter
- Reports missing or malformed files
scripts/unpack_skill.py
Unpacks a .skill file to a directory:
python scripts/unpack_skill.py <source.skill> <destination-dir>
References
- references/skill-categories.md - Complete mapping of skill library categories and stacks
- references/agent-templates.md - Templates for creating engineer and quality agents