project-bootstrapping
Overview
Sets up new projects or improves existing projects with development best practices, tooling, documentation, and workflow automation.
When to Use
- "set up a new project"
- "bootstrap this project"
- "add best practices"
- "improve project structure"
- "set up development tooling"
- "initialize project properly"
What It Sets Up
1. Project Structure
- Standard directories (docs/, .github/, .cursor/, .claude/)
- Logical file organization
- Structure improvements
2. Git Configuration
- Comprehensive
.gitignore .gitattributesfor line endings/diffs- Git hooks (pre-commit, commit-msg)
- Branch protection patterns
3. Documentation
- Comprehensive
README.md CONTRIBUTING.md- Code documentation (JSDoc, docstrings)
CHANGELOG.mdstructure- Architecture docs if complex
- MIT License file
4. Testing Setup
- Identify/suggest testing framework
- Test structure and conventions
- Example/template tests
- Configure test runners
- Coverage reporting
- Testing scripts/commands
5. Code Quality Tools
- Linters (ESLint, Pylint, etc.)
- Formatters (Prettier, Black, etc.)
- Type checking (TypeScript, mypy, etc.)
- Pre-commit hooks for quality
- Editor configs (.editorconfig)
- Code quality badges
6. Dependencies Management
- Package manager configuration
- Organize dependencies
- Check security vulnerabilities
- Set up dependency updates (Dependabot, Renovate)
- Create lock files
- Document dependency choices
7. Development Workflow
- Useful npm scripts / Makefile targets
- Environment variable templates (.env.example)
- Docker configuration if appropriate
- Development startup scripts
- Hot-reload / watch modes
- Document development workflow
8. CI/CD Setup
- GitHub Actions / GitLab CI config
- Automated testing
- Automated deployment (if applicable)
- Status badges
- Release automation
- Branch protection
Approach
Discovery Phase
Ask clarifying questions:
- Project type: New or existing?
- Primary purpose: Web app, library, CLI tool?
- Language/framework: JS/TS, Python, Go, etc.?
- Collaboration: Personal or team?
- Deployment target: Server, cloud, mobile, desktop?
- Preferences: Specific tools/frameworks?
- Scope: Full setup or specific areas?
Implementation Phase
- Analyze existing structure (if existing project)
- Create plan based on answers
- Show plan and get approval
- Implement systematically (one area at a time)
- Verify completeness
- Provide handoff documentation
Customization
Adapts to:
- Language ecosystem: Node.js vs Python vs Go vs Rust
- Project size: Small script vs large app
- Team size: Solo vs collaborative
- Maturity: Startup speed vs enterprise standards
Success Criteria
- All standard files present and configured
- Clear and complete documentation
- Documented development workflow
- Automated quality tooling (pre-commit hooks)
- Easy test execution
- Follows language/framework conventions
- Quick developer onboarding
- No obvious best practices missing
Templates
- Node.js/TypeScript web app
- Python CLI tool
- Python web API (FastAPI/Flask)
- React/Next.js app
- Go service
- Rust CLI/library
Scope Control
- Full bootstrap: Everything from scratch
- Partial setup: Specific areas only (e.g., "just add testing")
- Improvement pass: Enhance existing project
- Audit + fix: Check what's missing and add it
More from kjgarza/marketplace-claude
vscode-extension-builder
Comprehensive guide for creating VS Code extensions from scratch, including project scaffolding, API usage, activation events, and packaging. Use when user wants to create/build/generate/develop a VS Code extension or plugin, asks about VS Code extension development, needs help with VS Code Extension API, discusses extension architecture, wants to add commands/webviews/language support, or mentions scaffolding a VS Code project.
94detect-code-smells
Detect common code smells and anti-patterns providing feedback on quality issues a senior developer would catch during review. Use when user opens/views code files, asks for code review or quality assessment, mentions code quality/refactoring/improvements, when files contain code smell patterns, or during code review discussions.
10scientific-visualization
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
9searching-academic-outputs-with-dimensions
Search for academic literature, empirical evidence, and scholarly research using the Dimensions database. Use when seeking research papers to support product decisions, find empirical studies, conduct literature reviews, explore funding patterns, validate hypotheses with academic sources, or discover research trends. Supports publications, grants, patents, clinical trials, and researcher profiles. Triggers on requests for "academic evidence", "empirical research", "find studies", "literature search", or "research to support decisions".
8scholar-evaluation
Systematic framework for evaluating scholarly and research work based on the ScholarEval methodology. This skill should be used when assessing research papers, evaluating literature reviews, scoring research methodologies, analyzing scientific writing quality, or applying structured evaluation criteria to academic work. Provides comprehensive assessment across multiple dimensions including problem formulation, literature review, methodology, data collection, analysis, results interpretation, and scholarly writing quality.
8project-scaffold
>
8