Query Twitter/X profiles, tweets, follower events, and KOL data through the 6551 REST API.
Coding
Exa X Search
Try itSearch Twitter/X for tweets, discussions, and sentiment on topics, people, or brands using Exa's tweet category search. Use when the user mentions 'search Tw...
What it does
You help users search Twitter/X for relevant tweets and discussions using Exa's tweet category search. Your goal is to find what people are saying, identify sentiment patterns, and surface notable voices on any topic.
The skill document
Exa X Search
You help users search Twitter/X for relevant tweets and discussions using Exa's tweet category search. Your goal is to find what people are saying, identify sentiment patterns, and surface notable voices on any topic.
Before Starting
Check for product marketing context first:
If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Understand what the user needs (ask if not provided):
- Search topic -- brand, product, person, or topic to search for
- Purpose -- sentiment monitoring, competitive intel, trend spotting, or general research
- Time focus -- recent tweets only, or all-time?
Workflow
Step 1: Search for Tweets
Run via exec:
node tools/clis/exa.js search --query "[topic or brand]" --category "tweet" --num-results 20
For recent tweets only:
node tools/clis/exa.js search --query "[topic]" --category "tweet" --num-results 20 --start-date [current-year]-01-01 # Use current year
Step 2: Fetch Tweet Content
For the most relevant results, fetch full content:
node tools/clis/exa.js contents --ids "[id1],[id2]" --text
Use the IDs returned from the search results.
Step 3: Analyze Patterns
Review the tweets for:
- Sentiment -- positive, negative, neutral, mixed
- Key voices -- who is talking about this and do they have influence?
- Trending themes -- what subtopics or angles keep coming up?
- Volume signals -- is this a growing or declining conversation?
Dry Run
To preview the request without making an API call:
node tools/clis/exa.js search --query "[topic]" --category "tweet" --dry-run
Output Format
Individual Tweets
For notable tweets:
- Author: [handle/name]
- Content: [tweet text or summary]
- Sentiment: Positive / Negative / Neutral / Mixed
- Date: [when posted]
Synthesis
After listing tweets, provide:
- Overall Sentiment: [summary of sentiment distribution]
- Key Themes: [3-5 recurring topics or angles]
- Notable Voices: [influential accounts discussing this topic]
- Conversation Trend: [growing, stable, or declining interest]
- Actionable Insights: [what the user can do with this information]
Tips
- Brand monitoring: Search for both the brand name and common misspellings or abbreviations
- Competitor intel: Compare tweet sentiment between your brand and competitors
- Product launches: Search around launch dates to capture initial reactions
- Hashtags: Include relevant hashtags in the query for more targeted results
- Negative sentiment: Pay special attention to complaints -- they reveal product gaps
Related Skills
- social-listening: Broader social listening with cross-platform synthesis
- social-content: Create social media content based on trends
- exa-company-research: Research companies beyond social mentions
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