
implement
by yonatangross
The Complete AI Development Toolkit for Claude Code — 159 skills, 34 agents, 20 commands, 144 hooks. Production-ready patterns for FastAPI, React 19, LangGraph, security, and testing.
SKILL.md
name: implement description: Full-power feature implementation with parallel subagents, skills, and MCPs. Use when implementing features, building features, creating features, or developing features. context: fork version: 1.1.0 author: OrchestKit tags: [implementation, feature, full-stack, parallel-agents] user-invocable: true
Implement Feature
Maximum utilization of parallel subagent execution for feature implementation.
Quick Start
/implement user authentication
/implement real-time notifications
/implement dashboard analytics
Phase 1: Discovery & Planning
1a. Create Task List
Break into small, deliverable, testable tasks:
- Each task completable in one focused session
- Each task MUST include its tests
- Group by domain (frontend, backend, AI, shared)
1b. Research Current Best Practices
# PARALLEL - Web searches (launch all in ONE message)
WebSearch("React 19 best practices 2026")
WebSearch("FastAPI async patterns 2026")
WebSearch("TypeScript 5.x strict mode 2026")
1c. Context7 Documentation
# PARALLEL - Library docs (launch all in ONE message)
mcp__context7__query-docs(libraryId="/vercel/next.js", query="app router")
mcp__context7__query-docs(libraryId="/tiangolo/fastapi", query="dependencies")
Phase 2: Skills Auto-Loading (CC 2.1.6)
CC 2.1.6 auto-discovers skills - no manual loading needed!
Relevant skills activated automatically based on task:
api-design-framework- REST/GraphQL patternsreact-server-components-framework- RSC, Server Actionstype-safety-validation- Zod, tRPC, Prismaunit-testing/integration-testing- Test patterns
Phase 3: Parallel Architecture Design (5 Agents)
Launch ALL 5 agents in ONE Task message with run_in_background: true:
| Agent | Focus |
|---|---|
| Plan | Architecture planning, dependency graph |
| backend-system-architect | API, services, database |
| frontend-ui-developer | Components, state, hooks |
| llm-integrator | LLM integration (if needed) |
| ux-researcher | User experience, accessibility |
# PARALLEL - All agents in ONE message
Task(subagent_type="Plan", prompt="...", run_in_background=True)
Task(subagent_type="backend-system-architect", prompt="...", run_in_background=True)
Task(subagent_type="frontend-ui-developer", prompt="...", run_in_background=True)
Task(subagent_type="llm-integrator", prompt="...", run_in_background=True)
Task(subagent_type="ux-researcher", prompt="...", run_in_background=True)
Phase 4: Parallel Implementation (8 Agents)
| Agent | Task |
|---|---|
| backend-system-architect #1 | API endpoints |
| backend-system-architect #2 | Database layer |
| frontend-ui-developer #1 | UI components |
| frontend-ui-developer #2 | State & API hooks |
| llm-integrator | AI integration |
| rapid-ui-designer | Styling |
| test-generator #1 | Test suite |
| prioritization-analyst | Progress tracking |
Phase 5: Integration & Validation (4 Agents)
| Agent | Task |
|---|---|
| backend-system-architect | Backend + database integration |
| frontend-ui-developer | Frontend + API integration |
| code-quality-reviewer #1 | Full test suite |
| security-auditor | Security audit |
Phase 5.5: Progress Notifications (CC 2.1.7)
CC 2.1.7 supports inline notification patterns for real-time progress updates:
Agent Completion Notifications
When subagents complete, track their progress:
# After parallel agent execution
for result in agent_results:
notification.inline(f"{result.agent}: {result.status}")
# Summary notification
notification.inline(f"Phase 5 complete: {len(agent_results)}/{expected} agents finished")
MCP Deferral Awareness
When MCPs are deferred due to context limits, adapt your workflow:
if mcp.deferred:
notification.inline("MCP tools deferred - using cached docs")
# Fall back to cached documentation
docs = load_cached_docs("react-19-patterns")
else:
# Normal MCP query
docs = mcp__context7__query_docs(...)
Progress Tracking Pattern
Use inline notifications for long-running phases:
[Phase 4] Starting: 8 parallel agents
[Phase 4] Complete: backend-system-architect (2.3s)
[Phase 4] Complete: frontend-ui-developer (3.1s)
[Phase 4] Complete: database-engineer (1.8s)
...
[Phase 4] Finished: 8/8 agents (12.5s total)
Phase 6: E2E Verification
If UI changes, verify with agent-browser:
agent-browser open http://localhost:5173
agent-browser wait --load networkidle
agent-browser snapshot -i
agent-browser screenshot /tmp/feature.png
agent-browser close
Phase 7: Documentation
Save implementation decisions to memory MCP for future reference:
mcp__mem0__add-memory(content="Implementation decisions...", userId="project-decisions")
Summary
Total Parallel Agents: 17 across 4 phases
Tools Used:
- context7 MCP (library documentation)
- mem0 MCP (decision persistence)
- agent-browser CLI (E2E verification)
Key Principles:
- Tests are NOT optional
- Parallel when independent (use
run_in_background: true) - CC 2.1.6 auto-loads skills from agent frontmatter
- Evidence-based completion
Related Skills
- explore: Explore codebase before implementing
- verify: Verify implementations work correctly
References
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レビュー
レビュー機能は近日公開予定です
