Deep Research Skill for Claude Code Enterprise grade research engine for Claude Code. Produces citation backed reports with source credibility scoring, multi provider search, and automated validation. Installation [安装/使用命令见下方] No additional dependencies required for basic usage. Optional: search cli (multi provider search) For aggregated search across Brave, Serper, Exa, Jina, and Firecrawl: [安装/使用命令见下方] Usage [安装/使用命令见下方] [安装/使用命令见下方] Research Modes Mode Phases Duration Best For Quick 3 2 5 min Initial exploration Standard 6 5 10 min Most research questions Deep 8 10 20 min Complex topics, critical decisions UltraDeep 8+ 20 45 min Comprehensive reports, maximum rigor Pipeline Scope → Plan → Retrieve (parallel search + agents) → Triangulate → Outline Refinement → Synthesize → Critique (with loop back) → Refine → Package Key features: Step 0 : Retrieves current date before searches (prevents stale training data year assumptions) Parallel retrieval : 5 10 concurrent searches + 2 3 focused sub agents returning structured evidence objects First Finish Search : Adaptive quality thresholds by mode Critique loop back : Phase 6 can return to Phase 3 with delta queries if critical gaps found Multi persona red teaming : Skeptical Practitioner, Adversarial Reviewer, Implementation Engineer (Deep/UltraDeep) Disk persisted citations : sources.json survives context compaction and continuation agents Output Reports saved to /Documents/[Topic] Research [Date]/ : Markdown (primary source of truth) HTML (McKinsey style, auto opened in browser) PDF (professional print via WeasyPrint) Reports 18K words auto continue via recursive agent spawning with context preservation. Quality Standards 10+ sources, 3+ per major claim Executive summary 200 400 words Findings 600 2,000 words each, prose first ( =80%) Full bibliography with URLs, no placeholders Automated validation: validate report.py (9 checks) + verify citations.py (DOI/URL/hallucination detec