Run autonomous deep research workflows with GPT Researcher
Use GPT Researcher to plan, gather, source, and assemble cited web or local research reports through a repeatable agent workflow.
npx skills add agentskillexchange/skills --skill run-autonomous-deep-research-workflows-with-gpt-researcher
Use GPT Researcher when an agent needs to turn a research question into a cited report instead of manually searching, opening tabs, and stitching notes together. The workflow plans subquestions, gathers web or local context, summarizes sources, and assembles a long-form report with citations. The boundary is deep research execution and report generation, not a generic search tool, browser scraper, or broad LLM application framework.
What this skill actually does
Inputs and prerequisites: Python 3.11+, GPT Researcher, LLM provider API key, Tavily or configured retriever.
Setup notes: Install with `pip install gpt-researcher`, configure provider and retriever API keys such as `OPENAI_API_KEY` and `TAVILY_API_KEY`, then run GPT Researcher from the package, app, Docker setup, or Claude Skill path documented upstream.
Source and verification boundary: use https://docs.gptr.dev as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.
Framework fit: publish this as a Multi-Framework workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.