screen-recommendation-loopBuild and run a low-friction movie/anime recommendation + follow-up loop. Use when a user wants long-term taste profiling from watched/unfinished/dropped fee...
Install via ClawdBot CLI:
clawdbot install GloryXia/screen-recommendation-loopGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 21, 2026
Integrate with platforms like Netflix or Hulu to offer a low-friction recommendation loop that adapts to user viewing habits. It suggests one title at a time, collects feedback on watched/unfinished/dropped status, and schedules follow-ups based on content type (e.g., movies after 7 days, anime after 30 days), enhancing user engagement without overwhelming them.
Deploy in libraries or educational institutions to recommend movies or anime from curated top lists (e.g., Douban/Bangumi). It helps patrons discover content with constrained randomness, updates preferences from feedback like partial or dropped status, and automates follow-up reminders to encourage completion and feedback collection.
Use on social media or community forums to run recommendation loops for user groups interested in movies and anime. It picks titles from mixed sources, collects short feedback via a fixed schema, and adapts future recommendations based on group preferences, fostering discussion and long-term engagement.
Apply in online stores selling DVDs, streaming subscriptions, or merchandise by recommending titles to customers. It balances exploitation of known preferences with exploration quotas, uses follow-up timing to prompt purchases or reviews, and updates weights from feedback like reject_this_title to refine inventory suggestions.
Incorporate into wellness apps to recommend therapeutic or mood-based content (e.g., using next mood feedback like healing or brainy). It suggests one title at a time, adapts based on user statuses like partial or dropped, and schedules follow-ups to support consistent engagement without burden, aiding in mental health routines.
Offer the skill as a premium feature in streaming apps or standalone platforms, charging a monthly fee for personalized recommendation loops. Revenue comes from user subscriptions, with tiers based on advanced analytics or integration with multiple content sources like Douban and Bangumi lists.
Provide basic recommendation functionality for free, with monetization through in-app purchases for enhanced features such as expanded candidate pools, detailed preference insights, or ad-free experiences. Revenue is generated from microtransactions and optional upgrades.
License the skill to businesses like media companies, libraries, or e-commerce sites for integration into their existing systems. Revenue comes from one-time licensing fees or annual contracts, with customization options for specific industries and data handling needs.
💬 Integration Tip
Ensure the skill uses a generic, privacy-safe schema (e.g., JSON or SQLite) without storing personal identifiers, and test with sample data before deployment to validate follow-up timing and preference updates.
Scored Apr 19, 2026
Real-time search engine supporting web search, vertical domain search, parallel batch search, and URL content extraction.
Manage Feishu (Lark) calendars by listing, searching, checking schedules, syncing events, and marking tasks with automated date extraction.
Process multiple items with progress tracking, checkpointing, and failure recovery.
cad reference tool
Search, install, and create OpenClaw skills using intelligent matching across built-in, local, and GitHub skill repositories.
Use when building CLI tools, implementing argument parsing, or adding interactive prompts. Invoke for CLI design, argument parsing, interactive prompts, progress indicators, shell completions.