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199-biotechnologies/claude-deep-research-skill

Enterprise-grade deep research skill for Claude Code with 8-phase pipeline, source credibility scoring, and automated validation. Outperforms OpenAI, Gemini, and Claude Desktop in quality and verification. observed · 2026-09-01

github.com/199-biotechnologies/claude-deep-research-skill · Python observed · 2026-09-01

Health v2 · maintenance only

51/100

  • Activity 76
  • Release rhythm 35
  • Longevity 21

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 302
  • days_rel: n/a
  • days_push: 144
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1005 stars · 110 forks observed · 2026-09-01

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Claude Code skill (plugin) that turns the agent into an enterprise-grade deep research engine with an 8-phase pipeline covering scoping, parallel retrieval, triangulation, synthesis, and critique loop-backs. It produces citation-backed Markdown, HTML, and PDF reports with source credibility scoring and automated citation/hallucination validation.

Use cases

  • deep research a topic and get a citation-backed report
  • research the current state of a technology using fresh web sources
  • compare two tools or stacks with sourced, verified analysis
  • generate executive-style HTML and PDF research reports automatically
  • detect hallucinated citations and verify DOI/URL sources in reports
  • aggregate searches across Brave, Serper, Exa, Jina, and Firecrawl
  • run multi-persona red-team critique over research findings

When to choose

  • You already work in Claude Code and want automated, rigorously cited research reports
  • You need long-form reports with validation loops, credibility scoring, and persistent citations that survive context compaction
  • You want multi-provider search aggregation with parallel retrieval and sub-agent evidence collection

When to avoid

  • You need a standalone research tool that works without Claude Code, since this is a skill requiring that host
  • You want quick one-shot answers; Deep and UltraDeep modes run 10-45 minutes
  • Your use is commercial or enterprise and licensing matters, as the repository has no license
  • You need general-purpose scraping or data collection rather than LLM-orchestrated research synthesis

Facets

plugin · maturity active

agent-framework rag prompt-engineering artificial-intelligence large-language-models cli python cross-platform claude-code claude-skill deep-research research-pipeline citation-verification source-credibility-scoring report-generation multi-provider-search hallucination-detection red-teaming ai-agents retrieval-augmented-generation macos

1 source

Member repositories

RepositoryRoleHealth v2
199-biotechnologies/claude-deep-research-skillmain51

For agents

markdown · JSON · MCP: product_card(name="199-biotechnologies/claude-deep-research-skill")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem