Help us improve
Share bugs, ideas, or general feedback.
From claude-commands
Conducts systematic academic and technical research using multiple search engines and AI reasoning, cross-validating sources and synthesizing findings into a structured summary with citations.
npx claudepluginhub jleechanorg/claude-commands --plugin claude-commandsHow this command is triggered — by the user, by Claude, or both
Slash command
/claude-commands:researchcommands/The summary Claude sees in its command listing — used to decide when to auto-load this command
## ⚡ EXECUTION INSTRUCTIONS FOR CLAUDE **When this command is invoked, YOU (Claude) must execute these steps immediately:** **This is NOT documentation - these are COMMANDS to execute right now.** **Use TodoWrite to track progress through multi-phase workflows.** ## 🚨 EXECUTION WORKFLOW ### Phase 0: Memory Search Context (parallel subagent) **Action Steps:** 1. **Run full memory search** in background using `/e` to gather context from ALL memory sources: 2. Display results as "📍 Prior Knowledge Found" — these should inform the research to avoid re-discovering known facts 3. Continu...
/researchConducts systematic research via four-phase methodology (discovery, investigation, synthesis, reporting) with multi-hop reasoning, web tools, and evidence synthesis. Produces cited reports with confidence levels.
/f5-researchConducts deep research on a topic using web search, documentation lookup, code analysis, and AI synthesis, producing structured reports with plans, findings, and evidence.
/sc-researchConducts deep web research with adaptive planning and multi-hop searches on a query, producing a markdown report with executive summary, citations, confidence levels, and sources.
/researchPerforms adaptive deep web research on a query with configurable --depth and --strategy options. Outputs markdown report with executive summary, analysis, confidence scores, and cited sources.
/deep_researchOrchestrates multi-agent deep research on a topic by analyzing complexity, generating sub-questions, spawning parallel research workers, and synthesizing cited reports.
/researchExecutes multi-agent research pipeline on given topic with Scout, Investigators, Deep Diver, Verifier, Synthesizer, and iterative Critic review to produce verified synthesized insights.
Share bugs, ideas, or general feedback.
When this command is invoked, YOU (Claude) must execute these steps immediately: This is NOT documentation - these are COMMANDS to execute right now. Use TodoWrite to track progress through multi-phase workflows.
Action Steps:
/e to gather context from ALL memory sources:
/e /memory_search "$ARGUMENTS"
Action Steps:
Action Steps: Ultra-depth Thinking Process:
Action Steps: Comprehensive Search Execution:
Action Steps: Sequential Thinking Applied to Research Results:
Action Steps: Research Summary with Methodology Transparency:
Purpose: Systematic research using multiple information sources with academic rigor
Usage: /research <topic> - Conduct comprehensive research on a specific topic
Before any research actions, capture today's date with a portable shell command and use it when checking source freshness or framing search queries:
CURRENT_DATE=$(date "+%Y-%m-%d")
The POSIX date invocation above works on both macOS and Ubuntu. If it ever fails (very rare), fall back to python3 -c "from datetime import datetime; print(datetime.now().strftime('%Y-%m-%d'))". Reference CURRENT_DATE explicitly when summarizing findings to flag material that may already be stale relative to today.
Default Execution: /research automatically combines:
/thinku - Ultra-depth sequential thinking for research planning and analysis/perp - Multi-engine search across Claude WebSearch, Perplexity, DuckDuckGo, Grok, and GeminiResearch Planning (/thinku) - Deep analytical thinking to:
Information Gathering (/perp) - Comprehensive multi-source search:
Analysis Integration (/thinku + findings) - Deep analytical processing:
Documentation - Structured research summary with methodology transparency
Primary Sources (via /perp):
Secondary Sources (via /perp):
Analysis Layer (via /thinku):
Query: /research microservices authentication patterns
Expected Execution Flow:
🧠 Research Planning (/thinku):
Analyzing research scope for microservices authentication patterns...
- Defining key research questions: scalability, security, implementation complexity
- Planning search strategy: official docs, industry practices, security considerations
- Identifying validation criteria: performance, security standards, adoption rates
🔍 Multi-source Information Gathering (/perp):
Searching across Claude, Perplexity, DuckDuckGo, Grok, and Gemini for: "microservices authentication patterns"
📊 Claude WebSearch Results:
[Latest industry trends and documentation]
🧠 Perplexity Deep Research:
[Cited comparisons with recency filters]
🔍 DuckDuckGo Results:
[Privacy-focused technical resources and alternatives]
🧠 Grok Intelligence:
[Real-time synthesis, trend analysis, and contrarian insights]
💎 Gemini Consultation:
[Development-focused technical guidance and code perspectives]
🧠 Deep Analysis Integration (/thinku):
Processing findings from all sources...
- Synthesizing common patterns across sources
- Evaluating trade-offs and implementation considerations
- Identifying consensus vs. conflicting recommendations
📋 Research Report: Microservices Authentication Patterns
🧠 Research Planning Analysis:
[Systematic breakdown of research approach and methodology]
📊 Multi-source Findings:
1. JWT Token-based Authentication
- Claude: [Latest industry standards]
- Perplexity: [Cited deep research synthesis]
- DuckDuckGo: [Community practices and tools]
- Grok: [Real-time synthesis of best practices]
2. Service-to-Service Authentication
- Claude: [Industry standards and recent updates]
- Perplexity: [Cited comparisons with recency filters]
- DuckDuckGo: [Alternative implementations and community tools]
- Grok: [Comparative analysis of authentication methods]
- Gemini: [Technical implementation guidance and code examples]
- Pattern analysis from /thinku integration
🧠 Strategic Analysis:
[Deep thinking synthesis of all findings with pattern recognition]
🎯 Evidence-based Recommendations:
[Actionable next steps derived from comprehensive analysis]
/thinku provides ultra-depth analysis throughout research process/perp delivers multi-engine information gatheringPerfect for:
vs. Other Commands:
/perp - Multi-engine search alone (without deep thinking integration)/thinku - Deep thinking alone (without comprehensive search)/arch - Architecture-specific design research/research = /thinku + /perp + integration - Full academic research methodologyMemory Enhancement: This command automatically searches memory context using Memory MCP for relevant past research methodologies, information sources, and research patterns to enhance research strategy and result quality. See CLAUDE.md Memory Enhancement Protocol for details.