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Found 106 Skills
USE FOR video search. Returns videos with title, URL, thumbnail, duration, view count, creator. Supports freshness filters, SafeSearch, pagination.
General-purpose web search using DuckDuckGo and AI-synthesized search engines. Use this skill for web searches, current information, fact-checking, news, and research on any topic where live internet data is needed. Supports all languages. Three modes: fast web results, AI-synthesized answers (IAsk.ai, great for deep questions and academic research), and Monica AI synthesis. Trigger on: "search for", "look up", "find information about", "what is the latest", "search the web", "find out about", "what happened with", "current status of", "recent news", "is X still true", "查一下", "搜索", "查资料", "上网查", "検索して", "調べて", any question requiring real-time or post-training web data. Do NOT trigger for: code exploration, local file analysis, codebase-internal questions, or well-established facts fully covered by training knowledge. Note: if the `agent-reach` skill is also available, prefer `ddg-search` for pure web search tasks; prefer `agent-reach` when the task involves social platforms (Twitter, Reddit, YouTube, WeChat, Bilibili, etc.) or platform-specific APIs.
Enables Claude to conduct comprehensive research using Gemini Deep Research for in-depth analysis and reports
Conduct in-depth web-based research on given topics, collect and organize materials for subsequent content creation. Automatically detect available web search tools (WebSearch or MCP search tools), fall back to DDGS when no tools are available. Output structured Markdown data summary with source citations.
Query job information on Boss Zhipin. This skill is used when users want to search for jobs on Boss Zhipin or filter positions by specific company sizes.
Use Google Serper Search API for web search. Activate this tool when the user says terms like "search", "look up", "find", "research", "investigate", "learn about", "inquire", or "retrieve".
A qualitative research assistant tool based on Braun & Clarke's Reflexive Thematic Analysis framework. Supports two input modes: (1) Provide raw interview text directly → The skill completes initial TA coding for each document, then proceeds to theme identification after summarization; (2) Provide existing initial coding pool → Directly enter the process of clustering, review, and naming suggestions. Outputs a structured candidate theme table, clearly marking codes with ambiguous boundaries and naming suggestions to be decided by researchers. This skill is triggered when users mention terms such as "thematic analysis", "theme coding", "help me cluster codes", "extract themes from codes", "Braun Clarke", "candidate themes", "how to categorize these codes into themes", "help me check the theme structure", "conduct thematic analysis on interviews". Note the difference from grounded-coding: grounded-coding focuses on category construction and theoretical relationships for procedural grounded theory; thematic-analysis focuses on semantic theme identification following the Braun & Clarke approach, outputting theme structures rather than theoretical propositions.
This skill should be used when user encounters "Tavily MCP error", "Tavily API key invalid", "web search not working", "Tavily failed", or needs help configuring Tavily integration.
Multi-route literature expansion + metadata normalization for evidence-first surveys. Produces a large candidate pool (`papers/papers_raw.jsonl`, target ≥1200) with stable IDs and provenance, ready for dedupe/rank + citation generation. **Trigger**: evidence collector, literature engineer, 文献扩充, 多路召回, snowballing, cited by, references, 元信息增强, provenance. **Use when**: 需要把候选文献扩充到 ≥1200 篇并补齐可追溯 meta（survey pipeline 的 Stage C1，写作前置 evidence）。 **Skip if**: 已经有高质量 `papers/papers_raw.jsonl`（≥1200 且每条都有稳定标识+来源记录）。 **Network**: 可离线（靠 imports）；雪崩/在线检索需要网络。 **Guardrail**: 不允许编造论文；每条记录必须带稳定标识（arXiv id / DOI / 可信 URL）和 provenance；不写 output/ prose。
Coordinate a research task by choosing the right workflow and dispatching to specialized agents. Use when the user has a broad or complex research request that may involve multiple steps.
Retrieve yourself, customers, customer business records, customer opportunities, customer contacts, leads, opportunities, tags, and users, and initiate queries via scripts.
You cannot access video content on your own. Use Cerul to search what was said, shown, or presented in tech talks, podcasts, conference presentations, and earnings calls. Use when a user asks about what someone said, wants video evidence, or needs citations from talks and interviews.