Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Added setup section, removed curl
What This Skill Does
Analyzes public sentiment for brands and products across Twitter, Reddit, and Instagram. Pulls up to 70K posts per query, exports bulk CSVs, and classifies them using Python/pandas. Covers 1.5B+ indexed posts.
Access to 1.5B+ indexed posts with bulk CSV export lets you analyze tens of thousands of posts in a single query, far beyond what manual social browsing or smaller monitoring tools support.
When to use it
- Tracking brand reputation after a product launch
- Detecting PR crises from spikes in negative mentions
- Comparing competitor sentiment across platforms
- Identifying recurring complaints buried in customer posts
- Monitoring marketing campaign reception in real time
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Analyze sentiment for Notion on Twitter over the last 30 days
- 1Calls xpoz.getTwitterPostsByKeywords with query 'Notion' and a 30-day date range
- 2Polls checkOperationStatus every 5 seconds until the operation completes
- 3Downloads the bulk CSV using the returned dataDumpExportOperationId
- 4Loads the CSV with pandas and classifies each post as positive, negative, or neutral using keyword scoring
- 5Computes an engagement-weighted sentiment score and extracts top themes and viral posts
Sentiment score 72/100 from 14,832 posts: 58% positive, 24% negative, 18% neutral — top negative theme is Performance (2K posts, 81% negative), top positive theme is UX (1.8K posts, 72% positive)
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.