Skip to content
Back to skills

Twitter Intelligence

ASecurity

Search tweets, analyze trends, monitor users, and gather social intelligence from Twitter/X through SandBase. Use when asked for Twitter research, social listening, trend analysis, influencer monitoring, sentiment tracking, or competitor social intelligence.

  • 200 stars
  • 0 votes
  • 1 copy
  • 5 views
  • Added September 5, 2026
ai-agentsapi

Works with

  • api
  • mcp

Security analysis

A100/100

Pro scans all 3 files and shows the line behind each finding

Scanned September 26, 2026

npx -y skills add sandbaseai/sandbase-skills --skill twitter-intelligence --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Twitter Intelligence?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Twitter Intelligence
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/sandbaseai-twitter-intelligence/badge)](https://www.skillsdirectory.com/skills/sandbaseai-twitter-intelligence)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: twitter-intelligence
description: Search tweets, analyze trends, monitor users, and gather social intelligence from Twitter/X through SandBase. Use when asked for Twitter research, social listening, trend analysis, influencer monitoring, sentiment tracking, or competitor social intelligence.
---

# Twitter Intelligence

Full-spectrum Twitter/X research and social listening through SandBase. Search public tweets, discover trends, analyze user profiles, and monitor discussions — all read-only, never posts or engages. Read [the API map](references/sandbase-api-map.md) before selecting a capability.

## Call SandBase capabilities

Use the capability identifiers below as discovery hints, not MCP tool names. Find the matching endpoint with `sandbase_discover(q: "<provider and capability>")`; use its returned `name` in `sandbase_inspect(name: "<returned name>")`. Read `inputSchema`, pricing, and `execute_as`, then call `sandbase_run` using `execute_as.arguments.name` and schema-defined `arguments`. If a `run_id` is returned, poll `sandbase_run_get(run_id: "<returned run_id>")` within the task budget until `completed` or `failed`; report pending or failed runs without resubmitting them automatically.

## Operating principles

- Use Twitter data as social signal evidence, not as representative public opinion.
- Separate observations (tweet volume, engagement, accounts posting) from interpretation (sentiment, trend direction).
- Preserve attribution: include tweet URLs, usernames, dates, and engagement metrics.
- Never post, like, retweet, follow, or engage on behalf of the user.
- Keep monitored accounts and strategy confidential unless sharing is requested.

## Workflow

### 1. Frame the research

Classify the request:
- **Trend discovery**: what's trending, emerging topics
- **Topic monitoring**: track discussions around a keyword or brand
- **User analysis**: profile, content, followers, engagement patterns
- **Sentiment tracking**: how people feel about a topic or brand
- **Competitor intelligence**: what competitors post and how audiences respond

### 2. Search tweets

Use `twitter_web_search_timeline` for keyword-based tweet discovery:
- Search for brand names, product names, hashtags, or topic phrases
- Use negative keywords to filter noise
- Compare search results for competitors side by side

Use `twitter_bulk_tweet_search` for higher-volume batch searches.

### 3. Discover trends

Use `twitter_web_trending` to find what's trending globally or by location.

### 4. Analyze users

Use `twitter_web_user_profile` for account details (bio, follower count, verified status).
Use `twitter_web_user_media` and tweet timeline tools for content analysis.
Use `twitter_web_user_followers` / `twitter_web_user_followings` for network analysis.

### 5. Deep-dive tweets

Use `twitter_web_tweet_detail` for specific tweet metrics and thread context.
Use `twitter_web_latest_post_comments` or `twitter_web_post_comments` for reply analysis.

## Output

Return: search scope, tweet volume summary, key accounts involved, sentiment signals, trend indicators, engagement patterns, and evidence gaps.

## Example tasks

- "What are people saying about [brand] on Twitter this week?"
- "Find trending topics in the AI/tech space right now."
- "Analyze @competitor's Twitter presence — posting frequency, engagement, top content."
- "Monitor mentions of [product launch] and summarize sentiment."
- "Who are the most influential voices discussing [topic] on Twitter?"

## Failure handling

- If SandBase is unavailable, report the failure and do not substitute a direct API.
- If searches return few results, try broader terms or related hashtags.
- If a user account is private/suspended, note the gap and continue with available data.

Files in this skill

  • SKILL.md3.3 KB
  • agents/openai.yaml239 B
  • references/sandbase-api-map.md1.2 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.