By jayteealao
AI-powered development tools. 19 agents, 10 commands, 8 skills, 3 MCP servers for code review, testing, documentation, brainstorming, and refactoring workflows with semantic code search.
Analyze errors, stack traces, and logs to identify root causes and recommend fixes
Enhance a plan with parallel research agents for each section to add depth, best practices, and implementation details
Generate comprehensive tests for specified files or features following project conventions
Have multiple specialized agents review a plan in parallel
Triage and categorize findings for the CLI todo system
Researches and synthesizes external best practices, official documentation, community standards, and open-source examples for any technology, framework, or development practice.
Gathers comprehensive documentation and best practices for frameworks, libraries, and dependencies including version-specific constraints and implementation patterns.
Analyzes git history to understand code evolution, trace origins of patterns, identify key contributors, and extract insights from commit history and blame data.
Searches .claude/solutions/ for institutional knowledge, patterns, and solved problems relevant to the current task using grep-first filtering.
Conducts thorough research on repository structure, documentation, architecture, conventions, templates, and implementation patterns to understand project best practices.
This skill provides patterns for safe, systematic refactoring including extract, rename, move, and simplification operations with proper testing and rollback strategies.
This skill should be used when clarifying WHAT to build before HOW, triggered by ambiguous requests or when the user wants to explore requirements and approaches collaboratively.
Capture solved problems as categorized documentation with YAML frontmatter for fast lookup
This skill should be used to refine brainstorm or plan documents before proceeding to the next workflow step. It applies when a brainstorm or plan document exists and the user wants to improve it.
This skill should be used when analyzing errors, stack traces, and logs to identify root causes and implement fixes.
External network access
Connects to servers outside your machine
Uses power tools
Uses Bash, Write, or Edit tools
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No model invocation
Executes directly as bash, bypassing the AI model
No model invocation
Executes directly as bash, bypassing the AI model
A Claude Code plugin that makes each unit of engineering work easier than the last.
/plugin marketplace add https://github.com/EveryInc/compound-engineering-plugin
/plugin install compound-engineering
Plan → Work → Review → Compound → Repeat
| Command | Purpose |
|---|---|
/workflows:plan | Turn feature ideas into detailed implementation plans |
/workflows:work | Execute plans with worktrees and task tracking |
/workflows:review | Multi-agent code review before merging |
/workflows:compound | Document learnings to make future work easier |
Each cycle compounds: plans inform future plans, reviews catch more issues, patterns get documented.
Each unit of engineering work should make subsequent units easier—not harder.
Traditional development accumulates technical debt. Every feature adds complexity. The codebase becomes harder to work with over time.
Compound engineering inverts this. 80% is in planning and review, 20% is in execution:
npx claudepluginhub jayteealao/compound-engineering-plugin --plugin compound-engineeringPersonalized coding tutorials that use your actual codebase for examples with spaced repetition quizzes
One command — `/wf`, the single SDLC entry point — driving a 10-stage lifecycle from intake through retro, with per-slice artifacts, runtime-truth verification, and PO-confirmed stack fingerprinting. 21 keys: the stages, standalone/drivers (design, probe, simplify, auto, yolo), navigation (status, recap), lifecycle (close), and routers (ship-plan, docs, observability). Code review is the `/wf review` key; design is `/wf design`; observability foundation is `/wf observability`; quick/standalone flows are `/wf intake` modes plus the `/wf probe` and `/wf simplify` keys.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Harness-native ECC operator layer - 67 agents, 278 skills, 94 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Matt Pocock's agent skills for real engineering — grilling, spec/ticket flows, TDD, code review, domain modelling and more. Plug-and-play, not vibe coding.