136 lines
5.4 KiB
Markdown
136 lines
5.4 KiB
Markdown
# 深度研究报告生成
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**GitHub**: [199-biotechnologies/claude-deep-research-skill](https://github.com/199-biotechnologies/claude-deep-research-skill) | **Gitea**: [mc-skills/199-biotechnologies--claude-deep-research-skill](http://192.168.0.109:3000/mc-skills/199-biotechnologies--claude-deep-research-skill)
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## 中文摘要
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企业级Claude Code研究引擎，支持Quick/Standard/Deep/UltraDeep四种模式，多来源并行搜索，自动验证引用，输出含完整参考文献的Markdown/HTML/PDF报告，适用于技术选型、复杂课题调研等场景。
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## 标签
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`研究` `报告生成` `多源搜索` `引用验证` `Claude Code技能`
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---
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## README 原文
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# Deep Research Skill for Claude Code
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Enterprise-grade research engine for Claude Code. Produces citation-backed reports with source credibility scoring, multi-provider search, and automated validation.
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## Installation
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```bash
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# Clone into Claude Code skills directory
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git clone https://github.com/199-biotechnologies/claude-deep-research-skill.git ~/.claude/skills/deep-research
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```
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No additional dependencies required for basic usage.
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### Optional: search-cli (multi-provider search)
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For aggregated search across Brave, Serper, Exa, Jina, and Firecrawl:
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```bash
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brew tap 199-biotechnologies/tap && brew install search-cli
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search config set keys.brave YOUR_KEY # configure at least one provider
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```
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## Usage
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```
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deep research on the current state of quantum computing
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```
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```
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deep research in ultradeep mode: compare PostgreSQL vs Supabase for our stack
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```
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## Research Modes
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| Mode | Phases | Duration | Best For |
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|------|--------|----------|----------|
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| Quick | 3 | 2-5 min | Initial exploration |
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| Standard | 6 | 5-10 min | Most research questions |
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| Deep | 8 | 10-20 min | Complex topics, critical decisions |
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| UltraDeep | 8+ | 20-45 min | Comprehensive reports, maximum rigor |
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## Pipeline
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Scope → Plan → **Retrieve** (parallel search + agents) → Triangulate → Outline Refinement → Synthesize → Critique (with loop-back) → Refine → Package
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Key features:
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- **Step 0**: Retrieves current date before searches (prevents stale training-data year assumptions)
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- **Parallel retrieval**: 5-10 concurrent searches + 2-3 focused sub-agents returning structured evidence objects
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- **First Finish Search**: Adaptive quality thresholds by mode
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- **Critique loop-back**: Phase 6 can return to Phase 3 with delta-queries if critical gaps found
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- **Multi-persona red teaming**: Skeptical Practitioner, Adversarial Reviewer, Implementation Engineer (Deep/UltraDeep)
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- **Disk-persisted citations**: `sources.json` survives context compaction and continuation agents
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## Output
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Reports saved to `~/Documents/[Topic]_Research_[Date]/`:
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- Markdown (primary source of truth)
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- HTML (McKinsey-style, auto-opened in browser)
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- PDF (professional print via WeasyPrint)
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Reports >18K words auto-continue via recursive agent spawning with context preservation.
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## Quality Standards
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- 10+ sources, 3+ per major claim
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- Executive summary 200-400 words
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- Findings 600-2,000 words each, prose-first (>=80%)
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- Full bibliography with URLs, no placeholders
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- Automated validation: `validate_report.py` (9 checks) + `verify_citations.py` (DOI/URL/hallucination detection)
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- Validation loop: validate → fix → retry (max 3 cycles)
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## Search Tools
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| Tool | When | Setup |
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|------|------|-------|
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| WebSearch | Default, always available | None |
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| Exa MCP | Semantic/neural search | MCP config |
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| search-cli | Multi-provider aggregation | `brew install search-cli` + API keys |
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## Architecture
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```
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deep-research/
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├── SKILL.md # Skill entry point (lean, ~100 lines)
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├── reference/
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│ ├── methodology.md # 8-phase pipeline details
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│ ├── report-assembly.md # Progressive generation strategy
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│ ├── quality-gates.md # Validation standards
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│ ├── html-generation.md # McKinsey HTML conversion
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│ ├── continuation.md # Auto-continuation protocol
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│ └── weasyprint_guidelines.md # PDF generation
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├── templates/
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│ ├── report_template.md # Report structure template
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│ └── mckinsey_report_template.html # HTML report template
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├── scripts/
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│ ├── validate_report.py # 9-check structure validator
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│ ├── verify_citations.py # DOI/URL/hallucination checker
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│ ├── source_evaluator.py # Source credibility scoring
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│ ├── citation_manager.py # Citation tracking
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│ ├── md_to_html.py # Markdown to HTML converter
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│ ├── verify_html.py # HTML verification
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│ └── research_engine.py # Core orchestration engine
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└── tests/
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└── fixtures/ # Test report fixtures
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```
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## Version History
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| Version | Date | Changes |
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|---------|------|---------|
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| 2.3.1 | 2026-03-19 | Template/validator harmonization, structured evidence, critique loop-back, multi-persona red teaming |
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| 2.3 | 2026-03-19 | Contract harmonization, search-cli integration, dynamic year detection, disk-persisted citations, validation loops |
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| 2.2 | 2025-11-05 | Auto-continuation system for unlimited length |
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| 2.1 | 2025-11-05 | Progressive file assembly |
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| 1.0 | 2025-11-04 | Initial release |
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## License
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MIT - modify as needed for your workflow.
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