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Found 11,817 Skills
Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation in five stages: audit the code, wrap the call, move the tools, add tracking, attach evaluators. Use when the user wants to externalize model/prompt configuration, move from direct provider calls (OpenAI, Anthropic, Bedrock, Gemini, Strands) to a managed config, or stage a full hardcoded-to-LaunchDarkly migration.
Agentic and machine-to-machine payments on Stellar. Covers x402 (HTTP 402 paid APIs via OZ Channels facilitator, fee-sponsored clients) and MPP (Machine Payments Protocol) in both Charge mode (per-request Soroban SAC) and Channel mode (off-chain commits, high-frequency). Defaults to USDC (SEP-41 SAC) on `stellar:testnet`/`stellar:pubnet` (CAIP-2). Use when selling a paid API to AI agents, building an x402 client, or designing a payment-channel architecture for high-frequency agent traffic.
Turn a completed experiment iteration into an honest, evidence-backed analysis — a markdown report and a portable data dump. Pulls run data via the tpc CLI, scores each task, clusters friction by root cause (with a transcript example per claim), compares arms, and closes on agent-readiness gaps. The natural companion to setup-experiment: setup → run → analyze. Trigger when users say: "analyze my experiment", "write the report", "experiment report", "analyze the results", "summarize the runs", "what happened in this iteration", "friction report", or "report gen".
The agentmemory HTTP REST API surface, the primary protocol for talking to the memory server. Use when calling agentmemory over HTTP, when MCP is unavailable and you need a fallback, or when integrating a host that does not speak MCP.
Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.
Multi-agent communication, task delegation, and coordination patterns. Use when working with multiple agents or complex collaborative workflows.
Multi-model consensus council for validation, research, and brainstorming. Spawns parallel judges with configurable perspectives and optional explorer sub-agents using runtime-native backends (Codex sub-agents or Claude teams). Modes: validate, brainstorm, research. Triggers: council, validate, brainstorm, critique, research, analyze, multi-model, consensus.
Spawn isolated agents for parallel task execution. Local mode auto-selects Codex sub-agents or Claude teams. Distributed mode uses tmux + Agent Mail (process isolation, persistence). Triggers: "swarm", "spawn agents", "parallel work".
Meta skill explaining the AgentOps workflow. Auto-injected on session start. Covers RPI workflow, Knowledge Flywheel, and skill catalog.
Expert in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous workflows.
Comprehensive knowledge of Claude Agent SDK architecture, tools, hooks, skills, and production patterns. Auto-activates for agent building, SDK integration, tool design, and MCP server tasks.
Multi-platform, multi-channel notification skill for AI code agents. Sends notifications (sound, macOS alert, Telegram, Email, Slack, Discord) when the agent needs user interaction or completes a task. Supports Claude Code, GitHub Copilot CLI, Cursor, Codex, and Aider.