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.
269 skills found
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.
Generate finite-difference stencils, select optimal numerical schemes for PDEs/ODEs, and perform truncation error analysis to improve simulation accuracy.
Collaborative PR review using a swarm of three specialized AI agents (Correctness, Health, UX) that discuss findings and reach consensus before posting a structured summary with inline comments.
Real-time observability dashboard for PAI multi-agent activity, featuring live WebSocket streaming, session tracing, and agent workflow debugging.
AI-powered creative visual prompt generator for posters, banners, product shots, and social media content.
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.
Operate Railway infrastructure: manage projects, services, databases, object storage, deployments, environments, variables, logs, and performance metrics.
A unified Solana development skill hub featuring multi-agent orchestration, progressive skill loading, and deep integrations for Anchor, Token-2022, DeFi protocols, and security auditing.
A comprehensive guide and reference for building, orchestrating, and deploying AI agents using the Google Agent Development Kit (ADK).
Transform AI agents into proactive partners using WAL Protocol, persistent memory buffers, and autonomous cron scheduling to anticipate needs and improve performance.
Implement Linkerd service mesh patterns for security, traffic policy management, and zero-trust networking in Kubernetes environments.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.