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/multi-agent-researcher

Conduct comprehensive research on any topic by coordinating 2-4 specialized researcher agents in parallel, then synthesizing findings into a detailed report via mandatory report-writer agent delegation (Full workflow documentation at docs/workflows/research-workflow.md)

From plugin
claude-multi-agent-research-system-skill
113 skills7 agents4 commands
Install
$ npx -y skills add ahmedibrahim085/Claude-Multi-Agent-Research-System-Skill --skill multi-agent-researcher --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/multi-agent-researcher

Context preview

The summary Claude sees to decide when to auto-load this skill.

Conduct comprehensive research on any topic by coordinating 2-4 specialized researcher agents in parallel, then synthesizing findings into a detailed report via mandatory report-writer agent delegation (Full workflow documentation at docs/workflows/research-workflow.md)

SKILL.md

multi-agent-researcher.SKILL.md
name: multi-agent-researcher
description: Conduct comprehensive research on any topic by coordinating 2-4 specialized researcher agents in parallel, then synthesizing findings into a detailed report via mandatory report-writer agent delegation (Full workflow documentation at docs/workflows/research-workflow.md)
allowed-tools: Task, Read, Glob, TodoWrite
version: 2.1.2

Multi-Agent Research Coordinator

Purpose

Transform complex research questions into comprehensive reports by: 1. Decomposing broad topics into 2-4 focused subtopics 2. Spawning specialized researcher agents in parallel 3. Synthesizing findings into cohesive final report 4. Saving structured outputs for reference

When to Use

Auto-invoke when user asks:

  • **Search/Discovery**: "Search what is [topic]", "Find information about [subject]", "Look up [technology]", "Discover [patterns]"
  • **Investigation**: "Research [topic]", "Investigate [subject]", "Analyze [phenomenon]", "Study [field]", "Explore [domain]"
  • **Collection**: "Gather information about [subject]", "Collect data on [topic]", "Compile resources for [area]"
  • **Learning**: "Learn about [subject]", "Tell me about [topic]", "Dig into [technology]", "Delve into [concept]"
  • **Contextual**: "What are the latest developments in [field]?", "Comprehensive analysis of [topic]", "Deep dive into [subject]", "State of the art in [domain]", "Best practices for [area]"

Do NOT invoke for:

  • Simple factual questions ("What is the capital of France?")
  • Decision evaluation ("Should I use X or Y?")
  • Code-related tasks ("Debug this function", "Write a script")

Orchestration Workflow

Phase 1: Query Analysis & Decomposition

**Step 1.1: Understand the Research Question** Analyze user's query to identify core topic, scope, and intent.

**Step 1.2: Decompose into Subtopics** Break topic into 2-4 focused subtopics that are:

  • Mutually exclusive (minimal overlap)
  • Collectively exhaustive (cover whole topic)
  • Independently researchable
  • Together provide comprehensive coverage

**Decomposition Patterns:**

**Temporal**: Past → Current → Future **Categorical**: Category 1, 2, 3 **Stakeholder**: Technical → Business → Policy → User **Problem-Solution**: Problem → Solutions → Gaps → Future **Geographic**: Region A → Region B → Comparison

**Step 1.3: Create Research Plan** Use TodoWrite to track:

- [ ] Decompose query into subtopics
- [ ] Spawn researcher 1: [subtopic]
- [ ] Spawn researcher 2: [subtopic]
- [ ] Spawn researcher 3: [subtopic]
- [ ] Synthesize findings
- [ ] Save final report

---

Phase 2: Parallel Research Execution

**Step 2.1: Spawn Researcher Agents in Parallel**

For each subtopic, create a Task tool call with:

subagent_type: "researcher"
description: "Research {subtopic name}"
prompt: "Research the following subtopic in depth:

**Subtopic**: {Subtopic name}
**Context**: Part of research on '{original topic}'
**Focus**: {Specific guidance}

Conduct thorough web research, gather authoritative sources, extract key findings, and save results to files/research_notes/{subtopic-slug}.md"

**Critical**: Spawn ALL researchers in parallel (multiple Task calls in same message), not sequentially.

**Step 2.2: Monitor Completion** Update TodoWrite as researchers complete.

**Step 2.3: Verify All Complete** Use Glob to confirm all files exist: `files/research_notes/*.md`

---

Phase 3: Synthesis & Report Generation

**⚠️ CRITICAL: ARCHITECTURAL ENFORCEMENT ACTIVE ⚠️**

**YOU DO NOT HAVE WRITE TOOL ACCESS** when this skill is active. The `allowed-tools` frontmatter explicitly EXCLUDES the Write tool to enforce proper workflow delegation.

**YOU CANNOT**:

  • ❌ Write synthesis reports yourself
  • ❌ Create files in files/reports/ directory
  • ❌ Bypass the report-writer agent

**YOU MUST**:

  • ✅ Spawn report-writer agent via Task tool
  • ✅ Delegate all synthesis and report writing to the agent
  • ✅ Read the completed report and deliver to user

---

**Step 3.1: Verify Research Completion**

1. Use Glob to confirm all research notes exist: `files/research_notes/*.md` 2. Verify count matches number of spawned researchers 3. If any missing: investigate and complete before synthesis

**Step 3.2: Spawn Report-Writer Agent (MANDATORY)**

**This is the ONLY synthesis approach** - there is no "Option A" or "Option B". You MUST use the report-writer agent because you lack Write tool permissions.

Task:
subagent_type: "report-writer"
description: "Synthesize research findings into comprehensive report"
prompt: "Synthesize research into comprehensive report:

**Original Question**: {user query}
**Subtopics Researched**: {list all subtopics}
**Notes Location**: files/research_notes/

## Your Tasks:
1. Read ALL research notes from files/research_notes/
2. Identify themes, patterns, and contradictions across notes
3. Synthesize findings into cohesive narrative
4. Cite sources from research notes
5. Add cross-cutting insights beyond individual notes
6. Save comprehensive report to files/reports/{topic-slug}_{timestamp}.md

## Report Structure:
- Executive Summary
- Key Findings (with evidence from research notes)
- Detailed Analysis by subtopic
- Cross-Cutting Themes
- Contradictions and Debates
- Gaps and Limitations
- Source Bibliography

Use the timestamp format: $(date +\"%Y%m%d-%H%M%S\") for the filename."

**Step 3.3: Monitor Agent Completion**

After spawning report-writer agent, wait for completion. The agent will:

  • Read all research notes
  • Synthesize findings
  • Write comprehensive report to files/reports/
  • Return completion message with file path

---

Phase 4: Deliver Results

**Step 4.1: Create User Summary**

# Research Complete: {Topic}

Comprehensive research completed with {N} specialized researchers.

## Key Findings
1. {Finding 1}
2. {Finding 2}
3. {Finding 3}

## Research Scope
{N} subtopics investigated:
- {Subtopic 1}
- {Subtopic 2}
- {Subtopic 3}

## Files Generated
**Research Notes**: `files/research_notes/
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Ships withclaude-multi-agent-research-system-skill

Orchestrated multi-agent research with architectural enforcement, parallel execution, and comprehensive audit trails.

Get the whole plugin