Data & AI

Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.

Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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.

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.

Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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.

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.

Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

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.

Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

This skill should be used when users need to create or debug Bloblang transformation scripts. Trigger when users ask about transforming data, mapping fields, parsing JSON/CSV/XML, converting timestamps, filtering arrays, or mention "bloblang", "blobl", "mapping processor", or describe any data transformation need like "convert this to that" or "transform my JSON".

This skill should be used when users need to create or fix Redpanda Connect pipeline configurations. Trigger when users mention "config", "pipeline", "YAML", "create a config", "fix my config", "validate my pipeline", or describe a streaming pipeline need like "read from Kafka and write to S3".

Android-specific code review workflow additions for Bitwarden Android. Provides change type refinements, checklist loading, and reference material organization. Complements bitwarden-code-reviewer agent's base review standards.

Hand off to a fresh Claude session. Use when context is full, you've finished a logical chunk of work, or need a fresh perspective. Work continues from hook.