Discover and list all URLs on a website without extracting content, via the Tavily CLI. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says "map the site", "find the URL for", "what pages are on", "list all pages", or "site structure". Faster than crawling — returns URLs only. Essential when you know the site but not the exact page. Combine with extract for targeted content retrieval.
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Discover URLs on a website without extracting content. Faster than crawling.
If tvly is not found on PATH, install it first:
curl -fsSL https://cli.tavily.com/install.sh | bash && tvly login
Do not skip this step or fall back to other tools.
See tavily-cli for alternative install methods and auth options.
# Discover all URLs
tvly map "https://docs.example.com" --json
# With natural language filtering
tvly map "https://docs.example.com" --instructions "Find API docs and guides" --json
# Filter by path
tvly map "https://example.com" --select-paths "/blog/.*" --limit 500 --json
# Deep map
tvly map "https://example.com" --max-depth 3 --limit 200 --json
| Option | Description |
|---|---|
--max-depth | Levels deep (1-5, default: 1) |
--max-breadth | Links per page (default: 20) |
--limit | Max URLs to discover (default: 50) |
--instructions | Natural language guidance for URL filtering |
--select-paths | Comma-separated regex patterns to include |
--exclude-paths | Comma-separated regex patterns to exclude |
--select-domains | Comma-separated regex for domains to include |
--exclude-domains | Comma-separated regex for domains to exclude |
--allow-external / --no-external | Include external links |
--timeout | Max wait (10-150 seconds) |
-o, --output | Save output to file |
--json | Structured JSON output |
Use map to find the right page, then extract it. This is often more efficient than crawling an entire site:
# Step 1: Find the authentication docs
tvly map "https://docs.example.com" --instructions "authentication" --json
# Step 2: Extract the specific page you found
tvly extract "https://docs.example.com/api/authentication" --json
extract or crawl for content.--instructions for semantic filtering when path patterns aren't enough.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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使用 AACT (Aggregate Analysis of ClinicalTrials.gov) PostgreSQL 数据库进行大批量临床试验历史分析与数据挖掘。触发场景包括：AACT 查询、临床试验批量分析、PostgreSQL 试验数据、全量 NCT 检索、试验数据挖掘、clinical trials data warehouse、疾病领域全景分析、设计相似试验匹配、跨年度试验趋势聚合。本 skill 通过 SQL 接口处理百万级试验记录，支持云端公共 PostgreSQL 服务（aact-db.ctti-clinicaltrials.org）和每日 dump 本地还原两种连接方式，自动检测并优先使用本地高性能模式。
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使用 AACT (Aggregate Analysis of ClinicalTrials.gov) PostgreSQL 数据仓库进行批量、历史、聚合性临床试验数据挖掘。Use this skill when the user requests bulk SQL analysis over the full clinical trials data warehouse — historical trial trends, disease landscapes, similar-design matching, or multi-year aggregations across hundreds of thousands of NCT records. 触发场景包括：AACT 查询、临床试验批量分析、PostgreSQL 试验数据、全量 NCT 检索、试验数据挖掘、历史试验分析、clinical trials data warehouse、SQL trials、bulk trial analysis、disease landscape、试验设计相似性匹配、跨年度聚合、sponsor/phase/country 多维统计。**与 clinical-trials-v2 差异**：本 skill 走批量 SQL · 离线大数据（PostgreSQL）；v2 走实时 API · 单查询。两者互补：单条 NCT 实时状态用 v2，百万级历史挖掘用本 skill。支持云端公共 PostgreSQL（aact-db.ctti-clinicaltrials.org · 零部署）和每日 dump 本地还原（高性能 · 离线）两种连接方式，自动检测优先用本地。跨平台（macOS/Linux/Windows）参数化 SQL 防注入，read-only 强制保护。
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Use when work produces a deliverable, factual claim, dataset, code change, decision, publication, deployment, automation, or irreversible action whose failure would matter; when the user asks for a quality gate, acceptance criteria, QA, completeness, validation, audit, evidence, preflight, release readiness, or a definition of done; or before claiming completion on medium- or high-risk work. Automatically decide whether a formal gate is warranted, derive task-specific pass/fail criteria, gather evidence, and block unsupported completion. Make sure to use this skill even when the user does not say "quality gate" if consequential work needs acceptance criteria or completion evidence. Skip formal gating for trivial, reversible, low-impact requests.
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Create a changeset file in .changeset/ that describes a user-facing change for the release notes
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Add a new competitor to the AI Visibility Tool Directory — researches the tool, generates data, takes a screenshot, and inserts into the codebase
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Add tree-sitter language support to codegraph end-to-end — wire the grammar + extractor, write tests, then benchmark extraction quality and retrieval value on 3 popular real-world repos. Use when the user runs /add-lang <language> or asks to add/support a new language (e.g. Lua, Elixir, Zig, OCaml) in codegraph.
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