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deep-research
// Systematic multi-phase web research producing thorough, cited reports
// Systematic multi-phase web research producing thorough, cited reports
| name | deep-research |
| description | Systematic multi-phase web research producing thorough, cited reports |
| metadata | {"zeptoclaw":{"requires":{}}} |
Use this skill when the user asks you to research a topic in depth, produce a report, or investigate something thoroughly. A single search query is NEVER enough for real research.
Start wide. Use web_search with varied phrasings to map the territory:
Example: For "state of AI agents in 2026":
web_search("AI agent frameworks 2026")web_search("autonomous AI agents market landscape")web_search("AI agent orchestration tools comparison")For each important subtopic from Phase 1:
web_fetch to read full articles (not just search snippets)Example:
web_search("LangGraph vs CrewAI vs AutoGen benchmark 2026")web_fetch("https://example.com/detailed-comparison-article")Ensure you have coverage across these 6 types of information:
Search specifically for any category you're missing.
Before writing your final answer, verify:
If any check fails, go back and search for what's missing.
Always use the actual current date in search queries for current events:
"AI agent news March 2026""AI agent news" (may return outdated results)"March 2026", "2026-03", "2026"After completing research, save key findings using longterm_memory:
setresearchThis allows you to recall findings in future conversations without re-researching.