research-topic

# research-topic Drive wet-mcp's `extract(action="agent")` to answer a research question end to end: one search round + concurrent extracts of the top hits + a single LLM synthesis pass that preserves numbered `[N]` citations matching the returned sources. Use this skill when: - The user asks an open-ended question that needs multiple sources. - "Summarise the current state of X." - "What's the latest on Y?" - "Compare approaches to Z." - The user needs a quoted, cited answer (the citations are first-class output, not an afterthought). Do NOT use this skill when: - The user already gave you a specific URL -- call `extract(action="extract")`. - The user wants a single search result list -- call `search(action="web")`. - The question is about library API documentation -- call `search(action="docs_query")` against a Tier 1 / locked stack. ## Steps 1. **Restate the question** to the user in 1-2 sentences (calibration: confirm scope before spending tokens). 2. **Pick `max_urls`** based on breadth: - 3-5 for a tight question (single technology, single timeframe). - 6-10 for a broad survey (multiple competitors, multi-year window). - Hard ceiling is 20 (cost guard). 3. **Pick `synthesis_model`** only if the user asked for a specific model. Otherwise omit and let wet auto-detect from `LLM_MODELS` / `GEMINI_API_KEY` / `OPENAI_API_KEY` / `XAI_API_KEY`. 4. **Call** ```text extract(action="agent", query="<question>", max_urls=<N>) ``` Optional kn...