deep-research-pipelineMulti-stage deep research with reflection loops, multi-query retrieval, LLM chunk selection, and citation integrity. Use when: deep research, literature revi...
Install via ClawdBot CLI:
clawdbot install vardhineediganesh877-ui/deep-research-pipelineGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
post → https://www.postgresql.org/docs/current/Calls external URL not in known-safe list
https://api.example.com/v1Uses known external API (expected, informational)
api.openai.comAudited Apr 27, 2026 · audit v1.0
Generated May 21, 2026
Use the Deep Research Pipeline to compare cloud platforms (e.g., Vercel, Netlify, Cloudflare Pages) for a 2026 landscape report. The pipeline multi-query searches for performance benchmarks, pricing updates, and feature comparisons, then synthesizes findings with citations.
Conduct a comprehensive literature review on quantum computing advancements as of 2026. The pipeline decomposes the topic into dimensions like hardware, algorithms, and applications, retrieves and selects relevant chunks from multiple sources, and produces a publication-quality report with gaps and contradictions.
Generate a competitive analysis report for a new market entrant by researching top competitors, market trends, and potential gaps. The pipeline's reflection loops ensure coverage of key dimensions, and the output can be formatted as a brief or full report for executives.
Verify claims about emerging treatments or medical devices by cross-referencing multiple clinical studies and authoritative sources. The pipeline surfaces contradictions and tracks citations, ensuring factual accuracy and traceability.
Offer tiered subscription plans (Basic, Pro, Enterprise) for generating reports, with higher tiers allowing more research cycles, longer reports, and priority processing. Revenue is recurring monthly or annually.
Provide a RESTful API endpoint that integrates the deep research pipeline into third-party applications (e.g., chatbots, analytics dashboards). Charge per query or token usage with volume discounts.
License the complete research pipeline as a white-label solution for large organizations (e.g., government agencies, corporate R&D) to deploy internally. Includes customization, on-premise option, and dedicated support.
💬 Integration Tip
Start in mock mode to test the pipeline locally before configuring your LLM provider. Use the provided CLI flags (e.g., --max-cycles, --format) to tailor output for your use case.
Scored May 21, 2026
Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required.
Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per t...
Seven-stage deep research pipeline for substantive research questions. Activates when user asks for deep research, 深度研究, research report, evidence-backed inv...
Perform deep research using Claude by autonomously gathering, analyzing, and synthesizing detailed information across diverse topics on request.
全生命周期质量保障专家,覆盖需求、设计、编码、测试、上线、运维全阶段的质量保障活动。 融合缺陷预防(逆向操作、依赖踏空、并发冲突、新旧兼容、状态迁移、因果判定)与质量度量、持续改进三大支柱, 帮助团队建立「预防-评审-度量-改进」的质量闭环,实现软件质量的持续提升。 Use when: - 需求/设计/编码/测试...
专家团自动组建技能(反面教材)。核心观点:AI只认事不认人,没必要模拟人类多角色协作方式。本技能演示为什么不需要这样做——AI应该直接面对任务,而不是模拟人类团队。触发词:组建专家团、专家协作、团队完成任务、自动组建团队、expert team、专家团、团队协作完成任务。