1.0k★by barneyjm
search – OpenClaw Skill
search is an OpenClaw Skills integration for coding workflows. Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code.
Skill Snapshot
| name | search |
| description | Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code. OpenClaw Skills integration. |
| owner | barneyjm |
| repository | barneyjm/search-2 |
| language | Markdown |
| license | MIT |
| topics | |
| security | L1 |
| install | openclaw add @barneyjm/search-2 |
| last updated | Feb 7, 2026 |
Maintainer

name: search description: "Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code."
Search Skill
Search the web and get relevant results optimized for LLM consumption.
Prerequisites
Tavily API Key Required - Get your key at https://tavily.com
Add to ~/.claude/settings.json:
{
"env": {
"TAVILY_API_KEY": "tvly-your-api-key-here"
}
}
Quick Start
Using the Script
./scripts/search.sh '<json>'
Examples:
# Basic search
./scripts/search.sh '{"query": "python async patterns"}'
# With options
./scripts/search.sh '{"query": "React hooks tutorial", "max_results": 10}'
# Advanced search with filters
./scripts/search.sh '{"query": "AI news", "topic": "news", "time_range": "week", "max_results": 10}'
# Domain-filtered search
./scripts/search.sh '{"query": "machine learning", "include_domains": ["arxiv.org", "github.com"], "search_depth": "advanced"}'
Basic Search
curl --request POST \
--url https://api.tavily.com/search \
--header "Authorization: Bearer $TAVILY_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"query": "latest developments in quantum computing",
"max_results": 5
}'
Advanced Search
curl --request POST \
--url https://api.tavily.com/search \
--header "Authorization: Bearer $TAVILY_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"query": "machine learning best practices",
"max_results": 10,
"search_depth": "advanced",
"include_domains": ["arxiv.org", "github.com"],
"chunks_per_source": 3
}'
API Reference
Endpoint
POST https://api.tavily.com/search
Headers
| Header | Value |
|---|---|
Authorization | Bearer <TAVILY_API_KEY> |
Content-Type | application/json |
Request Body
| Field | Type | Default | Description |
|---|---|---|---|
query | string | Required | Search query (keep under 400 chars) |
max_results | integer | 5 | Maximum results (0-20) |
search_depth | string | "basic" | ultra-fast, fast, basic, advanced |
topic | string | "general" | general, news, finance |
chunks_per_source | integer | 3 | Chunks per source (advanced/fast only) |
time_range | string | null | day, week, month, year |
include_domains | array | [] | Domains to include (max 300) |
exclude_domains | array | [] | Domains to exclude (max 150) |
include_answer | boolean | false | Include AI-generated answer |
include_raw_content | boolean | false | Include full page content |
include_images | boolean | false | Include image results |
Response Format
{
"query": "latest developments in quantum computing",
"results": [
{
"title": "Page Title",
"url": "https://example.com/page",
"content": "Extracted text snippet...",
"score": 0.85
}
],
"response_time": 1.2
}
Search Depth
| Depth | Latency | Relevance | Content Type |
|---|---|---|---|
ultra-fast | Lowest | Lower | NLP summary |
fast | Low | Good | Chunks |
basic | Medium | High | NLP summary |
advanced | Higher | Highest | Chunks |
When to use each:
ultra-fast: Real-time chat, autocompletefast: Need chunks but latency mattersbasic: General-purpose, balancedadvanced: Precision matters (default recommendation)
Examples
News Search
curl --request POST \
--url https://api.tavily.com/search \
--header "Authorization: Bearer $TAVILY_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"query": "AI news today",
"topic": "news",
"time_range": "day",
"max_results": 10
}'
Domain-Filtered Search
curl --request POST \
--url https://api.tavily.com/search \
--header "Authorization: Bearer $TAVILY_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"query": "Python async best practices",
"include_domains": ["docs.python.org", "realpython.com", "github.com"],
"search_depth": "advanced"
}'
Search with Full Content
curl --request POST \
--url https://api.tavily.com/search \
--header "Authorization: Bearer $TAVILY_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"query": "React hooks tutorial",
"max_results": 3,
"include_raw_content": true
}'
Finance Search
curl --request POST \
--url https://api.tavily.com/search \
--header "Authorization: Bearer $TAVILY_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"query": "AAPL earnings Q4 2024",
"topic": "finance",
"max_results": 10
}'
Tips
- Keep queries under 400 characters - Think search query, not prompt
- Break complex queries into sub-queries - Better results than one massive query
- Use
include_domainsto focus on trusted sources - Use
time_rangefor recent information - Filter by
score(0-1) to get highest relevance results
No README available.
Permissions & Security
Security level L1: Low-risk skills with minimal permissions. Review inputs and outputs before running in production.
Requirements
**Tavily API Key Required** - Get your key at https://tavily.com Add to `~/.claude/settings.json`: ```json { "env": { "TAVILY_API_KEY": "tvly-your-api-key-here" } } ```
FAQ
How do I install search?
Run openclaw add @barneyjm/search-2 in your terminal. This installs search into your OpenClaw Skills catalog.
Does this skill run locally or in the cloud?
OpenClaw Skills execute locally by default. Review the SKILL.md and permissions before running any skill.
Where can I verify the source code?
The source repository is available at https://github.com/openclaw/skills/tree/main/skills/barneyjm/search-2. Review commits and README documentation before installing.
