Persistent memory management for Claude Code via AutoMem. Use this skill when: Starting a session (recall project context, decisions, patterns) Making architectural decisions or library choices Fixing bugs (store root cause and solution) Learning user preferences or code style Debugging issues (search for similar past…
Select and connect the right vector-store backend for the vector-mcp MCP server — chromadb, postgres/pgvector, qdrant, couchbase, or mongodb — and supply the correct dbtype/connection parameters that every collection and search call needs. Use when the agent must decide which engine to target, wire up…
Guides embedding model migration in user without downtime. Use when someone asks 'how to switch embedding models', 'how to migrate vectors', 'how to update to a new model', 'zero-downtime model change', 'how to re-embed my data', or 'can I use two models at once'. Also use when upgrading model dimensions, switching…
Guides user search strategy selection. Use when someone asks 'should I use hybrid search?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're there', 'retrieval quality is not good enough', 'results too similar', 'need diversity', 'MMR', 'relevance feedback'…
Use when someone asks 'how to combine lexical and semantic retrieval', 'dense and sparse in one search?', 'how to combine multiple fields for retrieval?', 'payloads or sparse vectors for lexical?', 'which sparse embedding model to use?', 'BM25 vs SPLADE?'.
Use when adding, checking, or troubleshooting a local Qdrant recall sidecar for Hermes Agent skills or recent sessions. Prefer local-first indexing, dry-run previews, and privacy-preserving defaults.
Expert guide for building applications with Qdrant Edge — the embedded, offline-capable vector search engine for edge devices (robots, kiosks, mobile phones, IoT, home assistants). Use this skill whenever the user mentions Qdrant Edge, qdrant-edge-py, EdgeShard, on-device vector search, offline vector search, embedded…
Master orchestrator for the ULTRON system. Routes requests across memory layers, skill packs, hooks, and the AI Router (primary→fallback chain). Loads on every Ultron session via the SessionStart hook. Customize this file for your own workflows — the shipped version is a minimal starting template.
A personal memory system that stores text, images, files, and secrets in separate collections. It can find stored items by meaning rather than only by exact words.
Use when generating visual artifacts, interactive HTML/JS apps, web mockups, charts, images, or reports that need to be presented to the user over remote SSH sessions via a live browser preview.