web-search-tavily▌
jwynia/agent-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Web search with AI-optimized results, relevance scoring, and advanced filtering via Tavily API.
- ›Supports three topic types (general, news, finance) and two search depths (basic, advanced) with optional AI-generated answer summaries
- ›Includes domain filtering to include or exclude specific sites, time-range filtering (day, week, month, year), and configurable result counts
- ›Returns structured results with relevance scores, publication dates, and optional raw page content; supports both
Web Search (Tavily API)
Search the web using Tavily's AI-optimized search API. Returns high-quality, structured results with relevance scores and optional AI-generated summaries.
Note: This skill requires a Tavily API key. For basic web search using the agent's built-in capability, see web-search.
When to Use This Skill
Use this skill when:
- You need to find current information not in your training data
- The user asks about recent events, news, or updates
- You need to verify facts or find authoritative sources
- Research requires real-time web data
- Keywords mentioned: search, look up, find online, current, latest, news
Do NOT use this skill when:
- Information is already in your knowledge base and doesn't need verification
- The user asks about historical facts that don't change
- You're working with local files or code (use other tools)
- A more specific skill exists for the task (e.g., documentation lookup)
Prerequisites
Before using this skill, ensure:
- TAVILY_API_KEY environment variable is set with a valid API key
- Deno is installed (for running the search script)
- Internet access is available
Get a Tavily API key at: https://tavily.com
Quick Start
Run a simple search:
deno run --allow-env --allow-net=api.tavily.com scripts/search.ts "your search query"
Example with AI-generated answer:
deno run --allow-env --allow-net=api.tavily.com scripts/search.ts "React 19 new features" --answer
Script Usage
deno run --allow-env --allow-net=api.tavily.com scripts/search.ts [options] "query"
Options
| Option | Description | Default |
|---|---|---|
--answer |
Include AI-generated answer summary | false |
--depth <level> |
Search depth: basic or advanced |
basic |
--results <n> |
Number of results to return | 5 |
--topic <type> |
Topic type: general, news, or finance |
general |
--time <range> |
Time filter: day, week, month, or year |
none |
--include <domains> |
Only include these domains (comma-separated) | none |
--exclude <domains> |
Exclude these domains (comma-separated) | none |
--raw |
Include raw page content in results | false |
--json |
Output as JSON (for programmatic use) | false |
--help |
Show help message | - |
Search Parameters
Topic Types
- general (default): Broad web search across all content types
- news: Prioritizes news articles and current events
- finance: Focuses on financial information and market data
Search Depth
- basic (default): Fast search, good for most queries
- advanced: Deeper search with more comprehensive results (slower, higher API cost)
Time Range
Filter results by recency:
- day: Last 24 hours
- week: Last 7 days
- month: Last 30 days
- year: Last 365 days
Domain Filtering
Control which sites appear in results:
# Only search documentation sites
scripts/search.ts "React hooks" --include docs.react.dev,developer.mozilla.org
# Exclude social media
scripts/search.ts "AI news" --exclude twitter.com,reddit.com
Output Format
Human-Readable Output (default)
🔍 Search: "React 19 new features"
Found 5 results in 234ms
📝 AI Answer:
────────────────────────────────────────────────────────────
React 19 introduces several new features including...
────────────────────────────────────────────────────────────
1. React 19 Release Notes
https://react.dev/blog/2024/04/25/react-19
React 19 is now available on npm! This release includes...
Score: 0.987
2. What's New in React 19
https://example.com/react-19-features
A comprehensive overview of React 19's new features...
Score: 0.945
JSON Output (--json)
{
"query": "React 19 new features",
"results": [
{
"title": "React 19 Release Notes",
"url": "https://react.dev/blog/2024/04/25/react-19",
"content": "React 19 is now available on npm...",
"score": 0.987,
"published_date": "2024-04-25"
}
],
"answer": "React 19 introduces several new features...",
"response_time": 234
}
Result Fields
| Field | Type | Description |
|---|---|---|
title |
string | Page title |
url |
string | Source URL |
content |
string | Relevant excerpt from the page |
score |
number | Relevance score (0-1, higher is better) |
published_date |
string | Publication date (if available) |
raw_content |
string | Full page content (only with --raw) |
Examples
Example 1: Current Events Search
Scenario: Find recent news about a technology topic
scripts/search.ts "OpenAI GPT-5 announcement" --topic news --time week --answer
Expected output: Recent news articles about GPT-5, with an AI-generated summary
Example 2: Documentation Lookup
Scenario: Find specific technical documentation
scripts/search.ts "Deno deploy edge functions tutorial" --depth advanced --results 10
Expected output: Comprehensive results from documentation and tutorial sites
Example 3: Fact Verification
Scenario: Verify a specific claim or statistic
scripts/search.ts "world population 2024" --include un.org,worldbank.org,census.gov --json
Expected output: JSON results from authoritative sources for programmatic verification
Example 4: Financial Research
Scenario: Research market information
scripts/search.ts "NVIDIA stock analysis 2024" --topic finance --answer
Expected output: Financial analysis and market data with AI summary
Common Issues and Solutions
Issue: "TAVILY_API_KEY environment variable is not set"
Symptoms: Script exits immediately with API key error
Solution:
- Get an API key from https://tavily.com
- Set the environment variable:
export TAVILY_API_KEY="your-api-key-here" - Or run with the variable inline:
TAVILY_API_KEY="your-key" deno run --allow-env --allow-net=api.tavily.com scripts/search.ts "query"
Issue: "Invalid Tavily API key"
Symptoms: 401 authentication error
Solution:
- Verify your API key is correct (no extra spaces)
- Check if your API key has expired
- Verify your Tavily account is active
Issue: "Tavily API rate limit exceeded"
Symptoms: 429 error response
Solution:
- Wait a moment and retry
- Reduce request frequency
- Consider upgrading your Tavily plan for higher limits
Issue: No results returned
Symptoms: Empty results array
Solution:
- Try broader search terms
- Remove domain filters that might be too restrictive
- Check if the topic exists online
- Try
--depth advancedfor harder queries
Limitations
This skill has the following limitations:
- Requires active internet connection
- API rate limits apply based on your Tavily plan
- Results depend on Tavily's index coverage
- Cannot access paywalled or login-required content
- Real-time accuracy depends on Tavily's crawling frequency
- Maximum query length and result count have API limits
Related Skills
- research-workflow: For comprehensive research projects that use multiple searches with planning and synthesis
How to use web-search-tavily on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add web-search-tavily
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches web-search-tavily from GitHub repository jwynia/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate web-search-tavily. Access the skill through slash commands (e.g., /web-search-tavily) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★36 reviews- ★★★★★Pratham Ware· Dec 20, 2024
Solid pick for teams standardizing on skills: web-search-tavily is focused, and the summary matches what you get after install.
- ★★★★★Valentina Anderson· Dec 20, 2024
web-search-tavily has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Nia Lopez· Dec 12, 2024
Solid pick for teams standardizing on skills: web-search-tavily is focused, and the summary matches what you get after install.
- ★★★★★Yash Thakker· Nov 11, 2024
We added web-search-tavily from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sakura Ndlovu· Nov 11, 2024
web-search-tavily fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ren Martin· Nov 7, 2024
web-search-tavily reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Carlos Farah· Nov 3, 2024
We added web-search-tavily from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Valentina White· Oct 26, 2024
Registry listing for web-search-tavily matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Nia Haddad· Oct 22, 2024
web-search-tavily fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dhruvi Jain· Oct 2, 2024
web-search-tavily fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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