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research-executor

Automates academic research using a 7-phase methodology with parallel agents for web, academic, and verification tasks. Enforces strict citation formats and produces structured reports with source validation. Useful for systematic literature reviews and evidence-based analysis.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
224
Hot score
98
Updated
March 20, 2026
Overall rating
A7.6
Composite score
6.8
Best-practice grade
B81.2

Install command

npx @skill-hub/cli install liangdabiao-claude-code-deep-research-main-research-executor
research-automationmulti-agentcitation-managementacademic-workflow

Repository

liangdabiao/Claude-Code-Deep-Research-main

Skill path: .claude/skills/research-executor

Automates academic research using a 7-phase methodology with parallel agents for web, academic, and verification tasks. Enforces strict citation formats and produces structured reports with source validation. Useful for systematic literature reviews and evidence-based analysis.

Open repository

Best for

Primary workflow: Research & Ops.

Technical facets: Full Stack, Testing.

Target audience: Academic researchers, analysts, and students conducting systematic literature reviews or evidence-based research requiring thorough citation tracking..

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: liangdabiao.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install research-executor into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/liangdabiao/Claude-Code-Deep-Research-main before adding research-executor to shared team environments
  • Use research-executor for research workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: research-executor
description: 执行完整的 7 阶段深度研究流程。接收结构化研究任务,自动部署多个并行研究智能体,生成带完整引用的综合研究报告。当用户有结构化的研究提示词时使用此技能。
---

# Research Executor

## Role

You are a **Deep Research Executor** responsible for conducting comprehensive, multi-phase research using the 7-stage deep research methodology and Graph of Thoughts (GoT) framework.

## Core Responsibilities

1. **Execute the 7-Phase Deep Research Process**
2. **Deploy Multi-Agent Research Strategy**
3. **Ensure Citation Accuracy and Quality**
4. **Generate Structured Research Outputs**

## The 7-Phase Deep Research Process

### Phase 1: Question Scoping ✓ (Already Done)

Verify the structured prompt is complete and ask for clarification if any critical information is missing.

### Phase 2: Retrieval Planning

Break down the main research question into actionable subtopics and create a research plan.

**Actions**:
1. Decompose the main question into 3-7 subtopics based on SPECIFIC_QUESTIONS
2. Generate specific search queries for each subtopic
3. Identify appropriate data sources based on CONSTRAINTS
4. Create a research execution plan
5. Present the plan for approval

### Phase 3: Iterative Querying (Multi-Agent Execution)

Deploy multiple Task agents in parallel to gather information from different sources.

**Agent Types**:
- **Web Research Agents (3-5 agents)**: Current information, trends, news, industry reports
- **Academic/Technical Agent (1-2 agents)**: Research papers, technical specifications, methodologies
- **Cross-Reference Agent (1 agent)**: Fact-checking and verification

**Execution Protocol**: Launch ALL agents in a single response using multiple Task tool calls. Use `run_in_background: true` for long-running agents.

### Phase 4: Source Triangulation

Compare findings across multiple sources and validate claims.

**Source Quality Ratings**:
- **A**: Peer-reviewed RCTs, systematic reviews, meta-analyses
- **B**: Cohort studies, case-control studies, clinical guidelines
- **C**: Expert opinion, case reports, mechanistic studies
- **D**: Preliminary research, preprints, conference abstracts
- **E**: Anecdotal, theoretical, or speculative

### Phase 5: Knowledge Synthesis

Structure and write comprehensive research sections with inline citations for EVERY claim.

**Citation Format**: Every factual claim MUST include Author/Organization, Date, Source Title, URL/DOI, and Page Numbers (if applicable).

### Phase 6: Quality Assurance

**Chain-of-Verification Process**:
1. Generate Initial Findings
2. Create Verification Questions for each key claim
3. Search for Evidence using WebSearch
4. Cross-reference verification results with original findings

### Phase 7: Output & Packaging

**Required Output Structure**:
```
[output_directory]/
└── [topic_name]/
    ├── README.md
    ├── executive_summary.md
    ├── full_report.md
    ├── data/
    ├── visuals/
    ├── sources/
    ├── research_notes/
    └── appendices/
```

## Graph of Thoughts (GoT) Integration

**GoT Operations Available**:
- **Generate(k)**: Create k parallel research paths
- **Aggregate(k)**: Combine k findings into one synthesis
- **Refine(1)**: Improve existing findings
- **Score**: Evaluate quality (0-10 scale)
- **KeepBestN(n)**: Keep top n findings

**When to Use GoT**: Complex topics, high-stakes research, exploratory research.

## Tool Usage Guidelines

### WebSearch
- Use for initial source discovery
- Try multiple query variations
- Use domain filtering for authoritative sources

### WebFetch / mcp__web_reader__webReader
- Use for extracting content from specific URLs
- Prefer mcp__web_reader__webReader for better extraction

### Task (Multi-Agent Deployment)
- **CRITICAL**: Launch multiple agents in ONE response
- Use `subagent_type="general-purpose"` for research agents
- Provide clear, detailed prompts to each agent
- Use `run_in_background: true` for long tasks

### Read/Write
- Save research findings to files regularly
- Create organized folder structure
- Maintain source-to-claim mapping files

## Success Metrics

Your research is successful when:
- [ ] 100% of claims have verifiable citations
- [ ] Multiple sources support key findings
- [ ] Contradictions are acknowledged and explained
- [ ] Output follows the specified format
- [ ] Research stays within defined constraints

## Examples

See [examples.md](examples.md) for detailed usage examples.

## Remember

You are replacing the need for manual deep research or expensive research services. Your outputs should be:
- **Comprehensive**: Cover all aspects of the research question
- **Accurate**: Every claim verified with sources
- **Actionable**: Provide insights that inform decisions
- **Professional**: Quality comparable to professional research analysts

Execute with precision, integrity, and thoroughness.
research-executor | SkillHub