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Found 19 Skills
Spec-Driven Development methodology for AI-assisted development. Use when working in a LeanSpec project.
Evaluate how well a codebase supports autonomous AI development. Analyzes repositories across eight technical pillars (Style & Validation, Build System, Testing, Documentation, Dev Environment, Debugging & Observability, Security, Task Discovery) and five maturity levels. Use when users request `/readiness-report` or want to assess agent readiness, codebase maturity, or identify gaps preventing effective AI-assisted development.
Transform legacy codebases into AI-ready projects with Claude Code configurations. Use when (1) analyzing old projects to generate AI coding configurations, (2) creating CLAUDE.md, skills, subagents, slash commands, hooks, or rules for existing projects, (3) user wants to enable vibe coding for a codebase, (4) onboarding new team members with AI-assisted development, (5) user mentions "make project AI-ready", "generate Claude config", or "create coding standards for AI".
Analyzes, generates, and enhances CLAUDE.md files for any project type using best practices, modular architecture support, and tech stack customization. Use when setting up new projects, improving existing CLAUDE.md files, or establishing AI-assisted development standards.
BAZDMEG Method workflow checkpoint system for AI-assisted development. Enforce quality gates at three phases: pre-code, post-code, and pre-PR. Use when: (1) starting a new feature or bug fix, (2) finishing AI-generated code before review, (3) preparing a pull request, (4) running a planning interview, (5) auditing automation readiness, (6) preventing AI slop, (7) session bootstrap, (8) source rank, (9) domain gates, (10) bugbook. Triggers: 'bazdmeg', 'pre-code checklist', 'post-code checklist', 'pre-PR checklist', 'planning interview', 'quality gates', 'session bootstrap', 'source rank', 'domain gates', 'bugbook'.
Modular Code Organization
Compound Engineering workflow for AI-assisted development. Use when planning features, executing work, reviewing code, or codifying learnings. Follows the Plan → Work → Review → Compound loop where each unit of engineering makes subsequent work easier. Triggers on: plan this feature, implement this, review this code, compound learnings, create implementation plan, systematic development.
Conversational SDD (Specification-Driven Development) guidance skill based on OpenSpec. It is automatically triggered when a user describes development requirements, and guides the user through the entire SDD process via conversations without any manual command input.
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
Interactive three-part onboarding for new team members to the Trellis AI-assisted workflow system. Covers core philosophy (AI memory, project-specific knowledge, context drift), system structure and command deep-dives, real-world workflow examples, and guideline customization. Use when a new developer joins the project, someone needs to understand the Trellis workflow, or project guidelines need initial setup.
Configure AI coding agents like Cursor, GitHub Copilot, or Claude Code with project-specific patterns, coding guidelines, and MCP servers for consistent AI-assisted development.
Comprehensive guide for AI-assisted vibe coding. Use when the user wants to build applications through natural language prompts using tools like Lovable, Cursor, Replit, or Bolt. Includes best practices, pitfall awareness, tool-specific guidance, architectural decision support, and MVP scope definition with a bias toward cutting features aggressively to ship faster.