Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
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See how to installReview the instructions the agent will receive before you install.
Web search returning LLM-optimized results with content snippets and relevance scores.
If tvly is not found on PATH, use the bundled startup dependency setup or install it with:
uv tool install tavily-cli
If search asks for authentication, run:
tvly login
tvly search "your query" --json
tvly search "quantum computing" --depth advanced --max-results 10 --json
tvly search "AI news" --time-range week --topic news --json
tvly search "SEC filings" --include-domains sec.gov,reuters.com --json
tvly search "react hooks tutorial" --include-raw-content --max-results 3 --json
| Option | Description |
|---|---|
--depth | ultra-fast, fast, basic (default), advanced |
--max-results | Max results, 0-20 (default: 5) |
--topic | general (default), news, finance |
--time-range | day, week, month, year |
--start-date | Results after date (YYYY-MM-DD) |
--end-date | Results before date (YYYY-MM-DD) |
--include-domains | Comma-separated domains to include |
--exclude-domains | Comma-separated domains to exclude |
--country | Boost results from country |
--include-answer | Include AI answer (basic or advanced) |
--include-raw-content | Include full page content (markdown or text) |
--include-images | Include image results |
--include-image-descriptions | Include AI image descriptions |
--chunks-per-source | Chunks per source (advanced/fast depth only) |
-o, --output | Save output to file |
--json | Structured JSON output |
--include-raw-content when full page text is needed.--include-domains to focus on trusted sources.--time-range for recent information.echo "query" | tvly search - --jsonNo reviews yet. Tell others what you thought.
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Text-to-speech conversion using `uvx edge-tts` for generating audio from text. Use when (1) User requests audio/voice output with the "tts" trigger or keyword. (2) Content needs to be spoken rather than read (multitasking, accessibility, driving, cooking). (3) User wants a specific voice, speed, pitch, or format for TTS output.
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Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in HyperFrames HTML. Use when asked to build any HTML-based video content, add captions or subtitles synced to audio, generate text-to-speech narration, create audio-reactive animation (beat sync, glow, pulse driven by music), add animated text highlighting (marker sweeps, hand-drawn circles, burst lines, scribble, sketchout), or add transitions between scenes (crossfades, wipes, reveals, shader transitions). Covers composition authoring, timing, media, and the full video production workflow. For dev-loop CLI commands (init, lint, inspect, preview, render) see the hyperframes-cli skill; for asset preprocessing commands (tts, transcribe, remove-background) see the hyperframes-media skill.
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Use automatically for PDF tasks, including Chinese requests like 查看PDF, 读取PDF, PDF里写了什么, 总结PDF, 分析PDF, 提取PDF文字, 识别PDF内容, or questions about any .pdf file. Prefer text extraction with pdfplumber/pypdf first, then render pages with Poppler when layout, images, tables, stamps, watermarks, or scanned content matter.
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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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