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Found 5,783 Skills
Meta skill explaining the AgentOps workflow. Auto-injected on session start. Covers RPI workflow, Knowledge Flywheel, and skill catalog.
Create custom tools using the @tool decorator for domain-specific agents. Use when building agent-specific tools, implementing MCP servers, or creating in-memory tools with the Agent SDK.
Syncs skill metadata to AGENTS.md Auto-invoke sections. Trigger: When updating skill metadata (metadata.scope/metadata.auto_invoke), regenerating Auto-invoke tables, or running ./skills/skill-sync/assets/sync.sh (including --dry-run/--scope).
Configure popular MCP servers for enhanced agent capabilities
Amazon Bedrock AgentCore Evaluations for testing and monitoring AI agent quality. 13 built-in evaluators plus custom LLM-as-Judge patterns. Use when testing agents, monitoring production quality, setting up alerts, or validating agent behavior.
Amazon Bedrock AgentCore deployment patterns for production AI agents. Covers starter toolkit, direct code deploy, container deploy, CI/CD pipelines, and infrastructure as code. Use when deploying agents to production, setting up CI/CD, or managing agent infrastructure.
Manage work in Vibe Kanban (VK), the shared source of truth for agent tasks. Use when checking assigned work, creating/updating tasks, running heartbeat checks, scanning @mentions, or producing daily standup summaries. Triggers: "check the board", "what's on my plate", "create/update task", "heartbeat", "standup summary".
Implement ReasoningBank adaptive learning with AgentDBs 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.
This skill should be used when the user asks to "optimize with SIMBA", "use Bayesian optimization", "optimize agents with custom feedback", mentions "SIMBA optimizer", "mini-batch optimization", "statistical optimization", "lightweight optimizer", or needs an alternative to MIPROv2/GEPA for programs with rich feedback signals.
Optimize AGENTS.md and rules for token efficiency. Auto-invoked when user asks about improving agent instructions, compressing AGENTS.md, or making rules more effective.
Discover, create, and validate headless adapters for agent integration. Includes scaffolding tools and schema-driven compliance testing.
Enable efficient communication between Thai-language users and agents by translating Thai prompts into English in two modes and by preventing Thai text corruption in files. Use when the user writes in Thai, asks for Thai-to-English interpretation, wants token-efficient prompt rewriting, or reports mojibake/replacement-character issues such as U+FFFD in saved files.