Search X

Real-time X/Twitter search powered by xAI's Responses API and the x_search tool. Returns actual tweets with citations, engagement context, images, and direct links. No scraping, no cookies, no browser automation - just the xAI API.

Setup

Set your xAI API key:

openclaw config set skills.entries.search-x.apiKey "xai-YOUR-KEY"

Or use environment variable:

export XAI_API_KEY="xai-YOUR-KEY"

Get your API key at: https://console.x.ai

Responses API with x_search (RECOMMENDED)

The primary way this skill searches X is through the Responses API (POST /v1/responses) with the x_search tool. This is the recommended approach because xAI handles all search orchestration server-side.

How it works

POST https://api.x.ai/v1/responses
Authorization: Bearer $XAI_API_KEY
Content-Type: application/json

{
  "model": "grok-4-1-fast-non-reasoning",
  "tools": [{"type": "x_search"}],
  "input": "Find recent tweets about Claude Code tips"
}

Key advantages over manual chat/completions + search:

Server-side orchestration - Grok decides when and how to search X, no client-side tool loop needed
Automatic citations - every result includes source URLs pointing to actual tweets
Combined tools - you can pass x_search, web_search, and code_interpreter in the same request and Grok will use whichever tools are appropriate
Structured results - citations come back as structured objects with URLs, not inline text

Combining tools in one request

{
  "model": "grok-4-1-fast-non-reasoning",
  "tools": [
    {"type": "x_search"},
    {"type": "web_search"}
  ],
  "input": "What are people saying about the new React compiler on X, and what does the official documentation say?"
}

Grok will search X for social discussion and the web for official docs, then synthesize both into a single response with citations from each source.

Models

Model	Context	Price (in/out per 1M tokens)	Best For
grok-4.20-multi-agent-beta-0309	2M	$2 / $6	Complex multi-step research
grok-4.20-beta-0309-reasoning	2M	$2 / $6	Deep analysis with reasoning
grok-4-1-fast-reasoning	2M	$0.20 / $0.50	Fast search with reasoning
grok-4-1-fast-non-reasoning	2M	$0.20 / $0.50	Quick searches (cheapest)

Grok 4.20 Multi-Agent Beta

The grok-4.20-multi-agent-beta-0309 model uses multi-agent collaboration for complex research queries. Multiple Grok agents work together to break down the query, search from different angles, and synthesize findings. Use this when:

The query requires cross-referencing multiple topics or accounts
You need comprehensive research rather than a quick lookup
The user asks for analysis, comparison, or trend synthesis across many data points
Time and cost are less important than thoroughness

node {baseDir}/scripts/search.js --model grok-4.20-multi-agent-beta-0309 "comprehensive analysis of AI safety discourse evolution"

Model selection guidance

Default (quick searches): grok-4-1-fast-non-reasoning - cheapest, fastest, good for simple tweet lookups
Reasoning needed: grok-4-1-fast-reasoning - same price, adds chain-of-thought for better analysis
Image search: grok-4.20-beta-0309-reasoning - returns image results alongside tweets
Deep research: grok-4.20-multi-agent-beta-0309 - multi-agent for complex queries

Search Modes via x_search

The x_search tool supports four distinct search modes. Grok selects the appropriate mode automatically based on the query, but you can guide it with your prompt.

Keyword Search

Exact term matching. Best for finding tweets with specific phrases, hashtags, or terms.

node {baseDir}/scripts/search.js "Claude Code monorepo tips"

Grok searches for tweets containing the exact terms. Use quotes in the query for exact phrase matching.

Semantic Search

Meaning-based search. Best for finding tweets about a concept even when they don't use the exact words.

node {baseDir}/scripts/search.js "people frustrated with slow CI/CD pipelines"

Grok understands the intent and finds relevant tweets even if they use different terminology (e.g., "build times are killing me", "GitHub Actions taking forever").

User Search

Find accounts and their activity. Best for profile lookups and account discovery.

node {baseDir}/scripts/search.js --handles karpathy --days 30 "posts from @karpathy about transformers"

Returns account information, recent posts, and engagement patterns. Combine with topic filters to see what someone says about a specific subject.

Thread Fetch

Complete conversation threads. Best for reading full reply chains and discussions.

node {baseDir}/scripts/search.js --handles sama --days 7 "thread about AI regulation"

Grok reconstructs the full thread including replies, quote tweets, and the complete conversation context.

Commands

Basic Search

node {baseDir}/scripts/search.js "AI video editing"

Searches X for the query and returns tweets with usernames, content, dates, and direct links.

Filter by Time

node {baseDir}/scripts/search.js --days 7 "breaking news"
node {baseDir}/scripts/search.js --days 1 "trending today"
node {baseDir}/scripts/search.js --days 90 "product launch retrospective"

The --days flag sets how far back to search. Default is 30 days. Use --days 1 for "what happened today" queries, --days 7 for weekly roundups, and --days 90 for longer research.

Filter by Handles

node {baseDir}/scripts/search.js --handles @elonmusk,@OpenAI "AI announcements"
node {baseDir}/scripts/search.js --exclude @bots "real discussions"

Use --handles to restrict results to specific accounts. Use --exclude to filter out noise. Both accept comma-separated lists with or without the @ prefix.

Output Options

node {baseDir}/scripts/search.js --json "topic"        # Full JSON response with all metadata
node {baseDir}/scripts/search.js --compact "topic"     # Just tweets, no commentary or citations list
node {baseDir}/scripts/search.js --links-only "topic"  # Just X links, one per line

Model Selection

node {baseDir}/scripts/search.js --model grok-4.20-multi-agent-beta-0309 "complex research query"
node {baseDir}/scripts/search.js --model grok-4-1-fast-non-reasoning "quick text search"
node {baseDir}/scripts/search.js --model grok-4.20-beta-0309-reasoning "topic with images"

Modes

This skill supports six distinct modes based on what the user is asking for. The agent should pick the right mode based on the query.

Mode 1: Basic Tweet Search

When to use: User asks to "search X", "find tweets about", or "what are people saying about".

How to run:

node {baseDir}/scripts/search.js "query here"

Example queries:

"Search X for Claude Code tips"
"Find tweets about the new iPhone"
"What are people saying about Rust on X?"

Mode 2: Thread Reader

When to use: User asks to "read this thread", "expand this thread", or provides an X/Twitter URL and wants the full conversation.

How to run:

node {baseDir}/scripts/search.js "thread by @username about [topic] site:x.com"

For thread reading, construct a query that includes the author's handle and the thread topic. Grok's x_search will find the thread and return the full reply chain. If the user provides a direct tweet URL, extract the username and topic from the URL and search for it.

Example queries:

"Read this thread: https://x.com/karpathy/status/1234567890"
- Extract: search for "thread by @karpathy" with --handles karpathy --days 7
"Expand the thread from @levelsio about startups"
- Search: --handles levelsio "startups thread"

Tips for thread reading:

Use --handles to lock onto the thread author
Use --days 3 or --days 7 to narrow the time window
Ask Grok to "include all replies in the thread" in the query
If a thread is very long, Grok may summarize - run again with --compact for denser output

Mode 3: Trend Analysis

When to use: User asks "what's trending", "what's hot on X", or "what are the big conversations about [topic]".

How to run:

node {baseDir}/scripts/search.js --days 1 "trending [topic] most discussed"

For trend analysis, use a short time window (1-3 days) and include words like "trending", "viral", "most discussed", or "biggest conversations". Grok will identify high-engagement posts and common themes.

Example queries:

"What's trending on X about AI today?"
- Search: --days 1 "trending AI most discussed viral"
"What are the big conversations on Twitter this week about tech layoffs?"
- Search: --days 7 "tech layoffs biggest conversations most discussed"
"What's going viral about the election?"
- Search: --days 1 "election viral trending"

Output guidance for trends: When presenting trend results, organize them by theme. Group related tweets together and note which topics have the most engagement. Example format:

## Trending: [Topic] (last 24 hours)

### Theme 1: [Description]
- @user1: "tweet content" (high engagement)
  https://x.com/user1/status/123
- @user2: "related tweet"
  https://x.com/user2/status/456

### Theme 2: [Description]
- @user3: "tweet content"
  https://x.com/user3/status/789

Mode 4: Profile / Account Analysis

When to use: User asks "who is @handle on X", "what does @handle post about", or "show me recent posts from @handle".

How to run:

node {baseDir}/scripts/search.js --handles username --days 30 "posts from @username"

For profile analysis, use --handles to lock onto the account and search their recent activity. You can combine this with topic filters to see what someone has been saying about a specific subject.

Example queries:

"What has @elonmusk been posting about lately?"
- Search: --handles elonmusk --days 7 "recent posts from @elonmusk"
"Show me @karpathy's recent AI takes"
- Search: --handles karpathy --days 30 "AI machine learning deep learning"
"Who is @levelsio on X?"
- Search: --handles levelsio --days 30 "posts from @levelsio about"

Output guidance for profiles: When presenting profile results, lead with a summary of what the person mainly posts about, then show recent highlights:

## @username - Profile Summary

**Main topics:** AI, startups, indie hacking
**Posting frequency:** ~5-10 tweets/day
**Notable recent posts:**

1. @username (Mar 14): "tweet content"
   https://x.com/username/status/123

2. @username (Mar 12): "tweet content"
   https://x.com/username/status/456

Mode 5: Image Search

When to use: User asks for images, screenshots, photos, memes, or visual content from X. This is a key differentiator - Grok-4.20 can return image results.

How to run:

node {baseDir}/scripts/search.js --model grok-4.20-beta-0309-reasoning "images of [topic]"

IMPORTANT: You MUST use a grok-4.20 model for image searches. The grok-4-1-fast models do not return image results.

You can also combine Responses API + x_search with grok-imagine-image for image generation based on search context. For example, search for trending meme formats on X, then generate a new image in that style.

Example queries:

"Show me images people are sharing about the Mars landing on X"
- Search: --model grok-4.20-beta-0309-reasoning --days 3 "Mars landing images photos"
"Find memes about programming on X"
- Search: --model grok-4.20-beta-0309-reasoning --days 7 "programming memes funny"
"What screenshots are people sharing about Claude Code?"
- Search: --model grok-4.20-beta-0309-reasoning --days 7 "Claude Code screenshots"

Mode 6: Multi-Agent Research

When to use: User asks for comprehensive analysis, cross-topic comparison, or deep research that requires multiple search angles.

How to run:

node {baseDir}/scripts/search.js --model grok-4.20-multi-agent-beta-0309 "comprehensive query"

The multi-agent model breaks complex queries into sub-tasks, searches from multiple angles, and synthesizes findings. Best for:

"Compare what @OpenAI and @AnthropicAI communities are saying about model safety"
"Give me a comprehensive view of the React vs Svelte debate this month"
"Research the full timeline of the [event] controversy on X"

Prompt Caching

xAI supports prompt caching with a 90% reduction in input token costs on cached tokens. This is useful when:

Running repeated searches with similar system prompts or context
Monitoring a topic over time with the same base query
Building dashboards that poll X at regular intervals

Cached tokens are automatically detected by the API. Structure your requests so the system prompt and tool definitions stay consistent across calls - only the user query should change. The first request pays full price; subsequent requests with the same prefix get the 90% discount.

Batch API

The xAI Batch API (GA since January 2026) supports bulk search processing. Use it for:

Monitoring workflows - search 50 different topics/accounts in a single batch
Research pipelines - run many queries overnight at reduced cost
Competitive analysis - track multiple competitors' X activity in parallel

How to use batch search

POST https://api.x.ai/v1/batch
Authorization: Bearer $XAI_API_KEY

{
  "requests": [
    {
      "custom_id": "search-1",
      "method": "POST",
      "url": "/v1/responses",
      "body": {
        "model": "grok-4-1-fast-non-reasoning",
        "tools": [{"type": "x_search"}],
        "input": "Query 1"
      }
    },
    {
      "custom_id": "search-2",
      "method": "POST",
      "url": "/v1/responses",
      "body": {
        "model": "grok-4-1-fast-non-reasoning",
        "tools": [{"type": "x_search"}],
        "input": "Query 2"
      }
    }
  ]
}

Batch requests are processed asynchronously. Poll the batch status endpoint to check completion. Results are returned in the same order as the requests.

Output Formatting

When presenting search results to the user, format them as tweet cards with engagement context.

Standard Tweet Card Format

@username (Display Name) - Mar 14, 2026
"The full tweet content goes here, preserving the original text
exactly as posted."

Link: https://x.com/username/status/1234567890123456789

Compact Format (for large result sets)

- @username: "Tweet content truncated if needed..." (Mar 14)
  https://x.com/username/status/123

Links-Only Format

When the user just wants URLs (e.g., to open in a browser or pass to another tool):

https://x.com/user1/status/123
https://x.com/user2/status/456
https://x.com/user3/status/789

Key Formatting Rules

Always include the direct X link for every tweet
Preserve the original tweet text - do not paraphrase
Include the author's @handle on every tweet
When Grok returns engagement signals (likes, retweets, replies), include them
Group results by relevance, not chronologically, unless the user asks for a timeline
If no results are found, say so clearly and suggest alternate queries
Cap output at 10-15 tweets unless the user asks for more

Error Recovery

No API Key

If XAI_API_KEY is not set and no key is found in the config:

Error: No xAI API key found.
Set XAI_API_KEY in your environment or run:
  openclaw config set skills.entries.search-x.apiKey "xai-YOUR-KEY"
Get your key at: https://console.x.ai

Rate Limits (HTTP 429)

The xAI API has rate limits. If you hit a 429:

Wait 10-15 seconds and retry once
If still rate-limited, tell the user: "xAI API rate limit hit. Try again in a minute."
Do NOT retry more than once - the user can re-run manually

Authentication Failures (HTTP 401 / 403)

Tell the user their API key may be invalid or expired
Direct them to https://console.x.ai to check their key
Suggest: export XAI_API_KEY="xai-NEW-KEY"

Empty Results

If Grok returns no tweets:

Try broadening the time window: --days 90 instead of --days 7
Try removing handle filters
Try simpler query terms
Tell the user: "No tweets found for this query. Try broader search terms or a wider time range."

Timeout / Network Errors

Grok searches can take 5-15 seconds for complex queries - this is normal
Multi-agent queries may take 15-30 seconds - this is expected
If the request times out, retry once with a simpler query
If network is down, tell the user clearly

Environment Variables

Variable	Required	Default	Description
`XAI_API_KEY`	Yes	-	Your xAI API key from console.x.ai
`SEARCH_X_MODEL`	No	`grok-4-1-fast-non-reasoning`	Default model for searches
`SEARCH_X_DAYS`	No	`30`	Default time window in days

Example Usage in Chat

Simple search

User: "Search X for what people are saying about Claude Code" Action: Run node {baseDir}/scripts/search.js "Claude Code" Present: Tweet cards with links

Time-scoped search

User: "Find tweets from the last week about Rust vs Go" Action: Run node {baseDir}/scripts/search.js --days 7 "Rust vs Go"

Account-specific search

User: "What has @karpathy been posting about lately?" Action: Run node {baseDir}/scripts/search.js --handles karpathy --days 14 "posts from @karpathy"

Thread reading

User: "Read this thread: https://x.com/sama/status/1234567890" Action: Extract handle (sama), run node {baseDir}/scripts/search.js --handles sama --days 7 "thread"

Trend check

User: "What's trending about AI on X today?" Action: Run node {baseDir}/scripts/search.js --days 1 "AI trending most discussed viral"

Image search

User: "Show me images people are sharing about the new MacBook on X" Action: Run node {baseDir}/scripts/search.js --model grok-4.20-beta-0309-reasoning --days 7 "new MacBook images photos screenshots"

Multi-agent research

User: "Give me a comprehensive analysis of the AI safety debate on X this month" Action: Run node {baseDir}/scripts/search.js --model grok-4.20-multi-agent-beta-0309 --days 30 "AI safety debate comprehensive analysis all perspectives"

Multi-handle comparison

User: "What are @OpenAI and @AnthropicAI saying about AI safety?" Action: Run node {baseDir}/scripts/search.js --handles OpenAI,AnthropicAI --days 30 "AI safety"

Exclusion filter

User: "Search X for AI news but exclude bot accounts" Action: Run node {baseDir}/scripts/search.js --exclude bots,spam --days 7 "AI news"

Links for later

User: "Give me links to the best tweets about indie hacking this month" Action: Run node {baseDir}/scripts/search.js --links-only --days 30 "indie hacking best advice"

JSON for piping

User: "Get raw JSON of tweets about TypeScript" Action: Run node {baseDir}/scripts/search.js --json "TypeScript"

Batch monitoring

User: "Set up monitoring for 10 competitor accounts on X" Action: Use the Batch API to submit 10 queries at once, one per competitor handle

Tips for Best Results

Be specific with queries. "Claude Code tips for monorepos" beats "Claude Code" every time.
Use handle filters for signal. Following specific people cuts noise dramatically.
Match time window to intent. Breaking news = 1 day. Weekly roundup = 7 days. Research = 30-90 days.
Use grok-4.20 models for visual queries. They are the only models that return image results from X.
Use multi-agent for deep research. grok-4.20-multi-agent-beta-0309 excels at multi-angle analysis.
Combine modes. Search for a topic, find an interesting thread, then read that thread in full.
Use --compact for scanning. When you need to review many tweets quickly, compact mode strips commentary.
Use --links-only for workflows. Pipe links to a browser opener, bookmark tool, or another skill.
Leverage prompt caching. Keep system prompts consistent across repeated searches to save 90% on input costs.
Use Batch API for bulk work. Monitoring, competitive analysis, and research pipelines benefit from batch processing.

Related Skills

/xai - Direct Grok chat without X search (general knowledge, coding, analysis)
/last30days - Research what happened in the last 30 days across multiple sources (not just X)
/parallel - Run multiple searches in parallel for faster research workflows