Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
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Agent skill for v3-performance-engineer - invoke with $agent-v3-performance-engineer
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Agent skill for v3-queen-coordinator - invoke with $agent-v3-queen-coordinator
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Agent skill for v3-memory-specialist - invoke with $agent-v3-memory-specialist
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GitHub PR/issue agent transcripts: redact, preview, and insert safely.
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Agent skill for user-tools - invoke with $agent-user-tools
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Agent skill for v3-integration-architect - invoke with $agent-v3-integration-architect
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Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
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Agent skill for topology-optimizer - invoke with $agent-topology-optimizer
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Agent skill for trading-predictor - invoke with $agent-trading-predictor
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Agent skill for tester - invoke with $agent-tester
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Add a redacted agent transcript section to GitHub PR or issue bodies during OpenClaw agent-created PR/issue workflows.
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Agent skill for test-long-runner - invoke with $agent-test-long-runner
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Automate Alpha Vantage tasks via Rube MCP (Composio). Always search tools first for current schemas.
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Automate All Images AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
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Automate Altoviz tasks via Rube MCP (Composio). Always search tools first for current schemas.
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Conversational AI-first interface with minimal controls, clear outcomes, and delegated task flows for agentic workflows.
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Requested GitHub PR/issue agent transcripts: redact, preview, and insert safely.
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Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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