memory-hygiene
Audit, prune, and maintain vector memory for Clawdbot. Prevents token waste, clears junk data, and automates memory hygiene via LanceDB maintenance.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
122 skills found
Audit, prune, and maintain vector memory for Clawdbot. Prevents token waste, clears junk data, and automates memory hygiene via LanceDB maintenance.
Kills stale claude-mem worker and MCP server processes to recover RAM and improve performance in memory-constrained environments like GitHub Codespaces.
A local RAG semantic memory system using Qdrant and Ollama. Ideal for recalling workspace files, notes, project decisions, and user preferences with high-relevance vector search.
Master memory forensics with techniques for acquisition, process analysis, and artifact extraction using Volatility 3 for incident response and malware analysis.
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
Virtual machine development expert focusing on bytecode design, stack-based/register-based VM implementation, memory management, and garbage collection.
Advanced context engineering system for orchestrating AI agents, memory management, and token optimization to improve long-term persistence and project intelligence.
Comprehensive health assessment tool for Continuous Claude components including skills, agents, hooks, and memory systems.
Enhance workflow efficiency by performing manual context compaction at logical task boundaries instead of relying on unpredictable auto-compaction.
A Git-backed memory store for agent skills. Download, version, edit, and share custom agent behaviors and procedural knowledge using a CLI.
Persistent, semantic long-term memory for AI agents. Save, query, and retrieve cross-session dialogues, decisions, and multimodal context using semantic compression.
An automated memory middleware for AI agents, implementing a Retrieve-Respond-Save loop to maintain long-term persistent context across conversations.