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Found 107 Skills
3-Phase Knowledge Search strategy for the RLM Factory ecosystem. Auto-invoked when tasks involve finding code, documentation, or architecture context in the repository. Enforces the optimal search order: RLM Summary Scan (O(1)) -> Vector DB Semantic Search -> Grep/Exact Match. Never skip phases.
Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vectorization pipelines.
Search 21st.dev component registry for production-ready React components. Finds components by natural language description, filters by framework and style system, returns ranked results with install instructions. Use when looking for UI components, finding alternatives to existing components, or sourcing design system building blocks.
MemPalace — Local AI memory with 96.6% recall. Semantic search, temporal knowledge graph, palace architecture (wings/rooms/drawers). Free, no cloud, no API keys.
Search and manage Alma's memory and conversation history. Use when the user asks about past conversations, personal facts, preferences, or anything that requires recalling information ("你知道我...吗", "我们之前聊过...", "你还记得...", "帮我找之前说的..."). Also used to store new memories and search through archived chat threads.
Use this skill to access Reddit's full data archive via reddapi.dev API. Features semantic search, subreddit discovery, and real-time trend analysis. Perfect for market research, competitive analysis, and niche opportunity discovery.
Search the web using Exa's AI-powered search API. Supports semantic search, content extraction, direct answers, and deep research with structured output.
Scaffold a complete knowledge system. Detects platform, conducts conversation, derives configuration, generates everything. Validates against 15 kernel primitives. Triggers on "/setup", "/setup --advanced", "set up my knowledge system", "create my vault".
Vector embeddings configuration and semantic search
Stores and retrieves persistent memory about records — contacts, companies, employees, members, and more. Handles memorization (single and batch with per-property AI extraction), semantic recall, entity digests, and data export. Use when storing data, syncing records, querying memory, or assembling context for personalization.
Search and manage Alma's memory and conversation history. Use when the user asks about past conversations, personal facts, preferences, or anything that requires recalling information ("do you know my...", "we talked about before...", "do you remember...", "help me find what we said about..."). Also used to store new memories and search through archived chat threads.