Deep Research 🔬

Deep web research with multi-round search, cross-verification, and structured reports with citations. Enhances web_search and web_fetch into a full research...

This skill appears coherent and implements what it claims: a planner → search → fetch → report pipeline using the platform's web_search/web_fetch tools and a local Python helper. Before installing, consider: 1) It runs a bundled Python script locally—if you want extra caution, inspect the full script (scripts/research.py) yourself or run it in a sandbox. 2) It will write temporary files and final reports by default under ~/.openclaw/workspace/research (or wherever RESEARCH_DIR points); set RESEARCH_DIR if you prefer a different location. 3) Deep mode can spawn parallel sub-agents (more autonomous activity); if you have strict limits on agent autonomy, avoid Deep or confirm platform-session policies. 4) No credentials are requested or needed. If you plan to run this on a sensitive host, either review the code line-by-line or run in an isolated environment.

Type: OpenClaw Skill Name: research-dive Version: 2.0.0 The skill bundle provides a structured multi-round research workflow using a Python script (scripts/research.py) to orchestrate search and fetch operations. It utilizes OpenClaw's built-in tools (web_search, web_fetch) and includes logic for source authority tiering and report generation. No evidence of data exfiltration, malicious execution, or prompt injection was found; the code and instructions (SKILL.md) are entirely consistent with the stated purpose of deep research.