atyachin skills on Remote OpenClaw

social-sentiment

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.

lead-generation

Finds people on Twitter, Instagram, and Reddit who are actively expressing problems your product solves, complaining about competitors, or asking for recommendations. Researches your product once, generates targeted queries, then scores and ranks discovered leads by purchase intent. Output includes lead context, a fit explanation, and a ready-to-review outreach draft.

xpoz-social-search

Searches Twitter, Instagram, and Reddit posts in real time against an index of 1.5B+ posts. Supports boolean queries, date filtering, user lookups, and subreddit discovery. CSV export handles bulk analysis up to 64K rows.

xpoz-setup

Sets up the Xpoz MCP server and handles OAuth authentication. Required before any other Xpoz skill can run. Supports browser-based login and a manual code flow for headless or remote servers.

instagram-search

Searches 400M+ Instagram posts, reels, and profiles by keyword, including video subtitles. Supports boolean queries, influencer discovery, and CSV export up to 64K rows. Runs through Xpoz MCP without requiring a Meta developer account or Instagram Graph API access.

social-intelligence

Connects AI agents to 1.5B+ indexed social posts across Twitter, Instagram, Reddit, and TikTok through a single MCP server. Supports keyword search with boolean queries, expert discovery, lead generation, sentiment analysis, influencer ranking, and bulk CSV export up to 64K rows per query.

twitter-api-alternative

Search over 1 billion tweets using keyword queries, boolean filters, or natural language, without a Twitter developer account. Supports profile lookups, user discovery by topic, follower/following lists, and CSV exports up to 64,000 rows. Also searches Instagram and Reddit through the same interface.

expert-finder

Searches Twitter and Reddit to identify people with demonstrated, technical knowledge in a given domain. Uses tiered keyword queries, from core terms to deep jargon, to find authors who discuss a topic beyond surface level. Ranks candidates by domain depth, posting consistency, and peer recognition, then produces a scored report with profile data and representative quotes.