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06e7c003e9
## Plugin Migration Added to pm-agent plugin: - /research: Deep web research with adaptive planning - /index-repo: Repository index (94% token reduction) - Total: 3 commands (pm, research, index-repo) ## Slash Commands Deleted Removed all 27 slash commands from ~/.claude/commands/sc/: - analyze, brainstorm, build, business-panel, cleanup - design, document, estimate, explain, git, help - implement, improve, index, load, pm, reflect - research, save, select-tool, spawn, spec-panel - task, test, troubleshoot, workflow ## Architecture Change Strategy: Minimal start with PM Agent orchestration - PM Agent = orchestrator (統括コマンダー) - Task tool (general-purpose, Explore) = execution - Plugin commands = specialized tasks when needed - Avoid reinventing the wheel (use official tools first) ## Files Changed - .claude-plugin/plugin.json: Added research + index-repo - .claude-plugin/commands/research.md: Copied from slash command - .claude-plugin/commands/index-repo.md: Copied from slash command - ~/.claude/commands/sc/: DELETED (all 27 commands) ## Benefits ✅ Minimal footprint (3 commands vs 27) ✅ Plugin-based distribution ✅ Version control ✅ Easy to extend when needed 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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name, description, category, complexity, mcp-servers, personas
| name | description | category | complexity | mcp-servers | personas | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| research | Deep web research with adaptive planning and intelligent search | command | advanced |
|
|
/sc:research - Deep Research Command
Context Framework Note: This command activates comprehensive research capabilities with adaptive planning, multi-hop reasoning, and evidence-based synthesis.
Triggers
- Research questions beyond knowledge cutoff
- Complex research questions
- Current events and real-time information
- Academic or technical research requirements
- Market analysis and competitive intelligence
Context Trigger Pattern
/sc:research "[query]" [--depth quick|standard|deep|exhaustive] [--strategy planning|intent|unified]
Behavioral Flow
1. Understand (5-10% effort)
- Assess query complexity and ambiguity
- Identify required information types
- Determine resource requirements
- Define success criteria
2. Plan (10-15% effort)
- Select planning strategy based on complexity
- Identify parallelization opportunities
- Generate research question decomposition
- Create investigation milestones
3. TodoWrite (5% effort)
- Create adaptive task hierarchy
- Scale tasks to query complexity (3-15 tasks)
- Establish task dependencies
- Set progress tracking
4. Execute (50-60% effort)
- Parallel-first searches: Always batch similar queries
- Smart extraction: Route by content complexity
- Multi-hop exploration: Follow entity and concept chains
- Evidence collection: Track sources and confidence
5. Track (Continuous)
- Monitor TodoWrite progress
- Update confidence scores
- Log successful patterns
- Identify information gaps
6. Validate (10-15% effort)
- Verify evidence chains
- Check source credibility
- Resolve contradictions
- Ensure completeness
Key Patterns
Parallel Execution
- Batch all independent searches
- Run concurrent extractions
- Only sequential for dependencies
Evidence Management
- Track search results
- Provide clear citations when available
- Note uncertainties explicitly
Adaptive Depth
- Quick: Basic search, 1 hop, summary output
- Standard: Extended search, 2-3 hops, structured report
- Deep: Comprehensive search, 3-4 hops, detailed analysis
- Exhaustive: Maximum depth, 5 hops, complete investigation
MCP Integration
- Tavily: Primary search and extraction engine
- Sequential: Complex reasoning and synthesis
- Playwright: JavaScript-heavy content extraction
- Serena: Research session persistence
Output Standards
- Save reports to
docs/research/[topic]_[timestamp].md - Include executive summary
- Provide confidence levels
- List all sources with citations
Examples
/sc:research "latest developments in quantum computing 2024"
/sc:research "competitive analysis of AI coding assistants" --depth deep
/sc:research "best practices for distributed systems" --strategy unified
Boundaries
Will: Current information, intelligent search, evidence-based analysis Won't: Make claims without sources, skip validation, access restricted content