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Found 107 Skills
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。
Retrieve yourself, customers, customer business records, customer opportunities, customer contacts, leads, opportunities, tags, and users, and initiate queries via scripts.
Web search via Tavily API (alternative to Brave). Use when the user asks to search the web / look up sources / find links and Brave web_search is unavailable or undesired. Returns a small set of relevant results (title, url, snippet) and can optionally include short answer summaries.
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.
Master the AI tools that accelerate research and information gathering. From market research to academic analysis, find insights faster and make better decisions. Use when "research, find information, academic papers, market research, competitive intelligence, fact check, research, information, analysis, academic, market-research" mentioned.
Research best-in-class products using Browser MCP and WebSearch
Use when you need concrete UI/UX inputs (palette, typography, landing patterns, UX/a11y constraints) to drive design or review. Searchable UI/UX design intelligence (styles, palettes, typography, landing patterns, charts, UX/a11y guidelines + stack best practices) backed by CSV + a Python search script. Triggers: UIUX/uiux, UI/UX, UX design, UI design, design system, design spec, color palette, typography, layout, animation, accessibility/a11y, component styling. Actions: search, recommend, review, improve UI.
Analyzes market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context). Use when asking about market breadth, uptrend ratios, or whether the market environment supports equity exposure. No API key required.
Intelligent Retrieval Assistant for Cangjie Language Documentation. Supports 4 search modes (Direct Search, PageIndex Intelligent Retrieval, Hybrid Mode, Exploratory Learning). It is used when users need to: (1) Query Cangjie syntax (variable declaration, function definition, generics, etc.), (2) Look up standard library APIs (String, Array, HashMap, etc.), (3) Learn about Cangjie features or get started with the language, (4) Conduct any documentation queries related to Cangjie/cangjie/cj. It uses four MCP tools: cangjie_docs_overview, cangjie_list_docs, cangjie_search, and cangjie_get_doc for intelligent retrieval.
Search the web using Perplexity AI. Use when needing to search, look up, research, find current information, best practices, compare technologies, or answer factual questions about tools and libraries.
NotebookLM CLI wrapper via `python3 {baseDir}/scripts/notebooklm.py` (backed by notebooklm-py). Use for auth, notebooks, chat, sources, notes, sharing, research, and artifact generation/download.