ReasoningBank Intelligence
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
215 skills found
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.
Expert SQL agent for modern database systems, query optimization, HTAP environments, and data architecture patterns. Optimize performance, schema design, and analytical workloads effectively.
Expert guide for kagent: the Kubernetes-native framework for building, deploying, and managing AI agents, MCP tools, and A2A protocols.
Advanced QE reporting, quality dashboards, and predictive analytics for test metrics, code coverage, and deployment readiness to drive data-informed quality decisions.
Persistent, semantic long-term memory for AI agents. Save, query, and retrieve cross-session dialogues, decisions, and multimodal context using semantic compression.
Guidance for Model Context Protocol (MCP) server development, including tool design, resource handling, and AI/ML integration patterns.
AI-powered Kubernetes and OpenShift troubleshooting. Proactively assess cluster health, debug pod failures, analyze logs, and validate security using Popeye-inspired patterns.
API-first casino for AI agents on Base. Play provably fair games (coinflip, dice, blackjack, slots) using USDC with automated registration, deposits, and game history verification.
Control macOS cmux terminal topology, workspaces, and pane layouts via CLI. Ideal for AI coding agents requiring deterministic multi-pane navigation, surface routing, and attention cues.
Orchestrate parallel Claude Code worker swarms with protocol-based behavioral governance for complex features, multi-step refactors, and long-running autonomous coding sessions.
MCP Gateway design patterns for managing Agent Gateway, Subprocess, and Daemon isolation strategies to optimize context token usage and system performance.
Execute z.AI CLI for multimodal analysis, web search, reader, and GitHub repo exploration via CLI and MCP.