Skill Detail
Run configurable multi-source deep research passes with Open Deep Research
Use Open Deep Research when an agent should run a configurable research job that searches, compresses, synthesizes, and writes a cited report across multiple model and search backends.
Research & ScrapingMulti-Framework
Research & Scraping
Multi-Framework
Security Reviewed
⭐ 11.1k GitHub stars
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill run-configurable-multi-source-deep-research-passes-with-open-deep-research
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Python, uv, model API credentials, one or more supported search tools
Install & setup
Clone the repository, create a virtual environment, install dependencies with uv sync, configure the .env file for model and search providers, then start the LangGraph development server to run research jobs.
Author
LangChain
Publisher
Organization
Last updated
Apr 16, 2026
Quick brief
Use Open Deep Research when the task is to execute a deep-research run that gathers sources, iterates on search, compresses findings, and produces a synthesized report. Invoke it instead of doing ad hoc web research in ordinary chat when you need a configurable research agent with interchangeable model providers, search tools, and MCP-compatible retrieval sources. The scope boundary is skill-shaped and concrete: this is a bounded research-run workflow, not a generic framework listing and not just a product card for LangChain or a hosted research app.