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Found 156 Skills
Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.
Use this skill when designing AI agent architectures, implementing tool use, building multi-agent systems, or creating agent memory. Triggers on AI agents, tool calling, agent loops, ReAct pattern, multi-agent orchestration, agent memory, planning strategies, agent evaluation, and any task requiring autonomous AI agent design.
Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.
Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases.
Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions.
Build multiple AI agents that work together. Use when you need a supervisor agent that delegates to specialists, agent handoff, parallel research agents, support escalation (L1 to L2), content pipeline (writer + editor + fact-checker), or any multi-agent system. Powered by DSPy for optimizable agents and LangGraph for orchestration.
Fan out a prompt to multiple AI coding agents in parallel and synthesize their responses.
Design tools that agents can use effectively. Use when creating new tools for agents, debugging tool-related failures, or optimizing existing tool sets.
Advanced information retrieval specialist combining systematic search strategies, multi-platform expertise, and precision filtering techniques. Excels at finding specific, high-quality information across diverse sources while minimizing noise and maximizing relevance.
Nassim Taleb's Antifragility framework applied to a business idea, system, or portfolio position. Spawns a team of specialist agents — Fat-Tail Detector, Fragility Auditor, Optionality Scout, Iatrogenics Checker, Skin-in-the-Game Auditor — who each apply a distinct lens from Taleb's Incerto to evaluate whether the subject is fragile, robust, or antifragile. The lead synthesizes into a convexity assessment: what's the payoff structure under disorder, where are the hidden tail risks, and the honest Taleb verdict. Use when the user says "taleb this", "is this fragile", "antifragility analysis", "what would Taleb think", "tail risk check", or proposes a business/system and wants structural risk analysis. Works standalone or after /munger for complementary analysis.