/research
Deep web research with adaptive planning and intelligent search
> /plugin marketplace add Galaxy-Dawn/claude-scholar > /plugin install claude-scholar@claude-scholar
How it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/research
Context preview
What this command does when you run it.
Deep web research with adaptive planning and intelligent search
Command definition
research.mdname: research
description: Deep web research with adaptive planning and intelligent search
category: command
complexity: advanced
mcp-servers: [tavily, sequential, playwright, serena]
personas: [deep-research-agent]
/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 `claudedocs/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
CRITICAL BOUNDARIES
**STOP AFTER RESEARCH REPORT**
This command produces a RESEARCH REPORT ONLY - no implementation.
**Explicitly Will NOT**:
- Implement findings or recommendations
- Write code based on research
- Make architectural decisions
- Create system changes based on research
**Output**: Research report (`claudedocs/research_*.md`) containing:
- Findings with sources
- Evidence-based analysis
- Recommendations (for human decision)
- Cited references
**Next Step**: After research completes, user decides next action. Use `/sc:design` for architecture or `/sc:implement` for coding.
Read more
name: research description: Deep web research with adaptive planning and intelligent search category: command complexity: advanced mcp-servers: [tavily, sequential, playwright, serena] personas: [deep-research-agent]
/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 `claudedocs/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
CRITICAL BOUNDARIES
**STOP AFTER RESEARCH REPORT**
This command produces a RESEARCH REPORT ONLY - no implementation.
**Explicitly Will NOT**:
- Implement findings or recommendations
- Write code based on research
- Make architectural decisions
- Create system changes based on research
**Output**: Research report (`claudedocs/research_*.md`) containing:
- Findings with sources
- Evidence-based analysis
- Recommendations (for human decision)
- Cited references
**Next Step**: After research completes, user decides next action. Use `/sc:design` for architecture or `/sc:implement` for coding.
Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding, experiments, writing, and publication.
Repo: Galaxy-Dawn/claude-scholar
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