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Found 7,228 Skills
Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agreement algorithms for reaching consensus among multiple agents.
AI agent development standards using golanggraph for graph-based workflows, langchaingo for LLM calls, tool integration, MCP, and LLM best practices (context compression, prompt caching, attention raising, tool response trimming).
This skill should be used when the user asks to "create chatbot", "virtual agent", "VA topic", "NLU", "conversation", "chat flow", "topic block", or any ServiceNow Virtual Agent development.
Use this skill to build, run, deploy, evaluate, and troubleshoot Go agents with Google's Agent Development Kit (`google.golang.org/adk`), including llmagent config, tools/integrations, callbacks/plugins, sessions/state/memory, workflows, streaming, MCP/A2A, and runtime/deployment patterns.
Create, optimize, update, and validate AGENTS.md files with maximum token efficiency. Use when the user asks to (1) create new AGENTS.md files for any repository, (2) optimize/condense existing AGENTS.md to reduce token count, (3) update/refresh AGENTS.md to sync with codebase changes, (4) validate AGENTS.md quality and completeness, or (5) improve AGENTS.md files to be more effective for AI agents. Always generates token-efficient, condensed output focused on actionable commands and patterns while maintaining model-agnostic language.
Add visual animations (cursor, typing, click effects) to AgentPulse-enabled React apps. Use when: showing users what AI is doing, adding visual feedback for agent actions, configuring element targeting for animations.
Coordinate multiple specialized Skills and Task Agents through parallel, sequential, swarm, hybrid, or iterative execution strategies. Use when orchestrating multi-worker workflows, managing dependencies, or optimizing complex task execution with quality gates.
Development skill from everything-agent-code
Best practices for using agent-browser with Kernel cloud browsers. Use when automating websites with agent-browser -p kernel, dealing with bot detection, iframes, login persistence, or needing to find Kernel browser session IDs and live view URLs.
Knowledge base for designing, reviewing, and linting agentic AI infrastructure. Use when: (1) designing a new agentic system and need to choose patterns, (2) reviewing an existing agentic architecture ADR or design doc for gaps/risks, (3) applying the lint script to an ADR markdown file to get structured findings, (4) looking up a specific agentic pattern (prompt chaining, routing, parallelization, reflection, tool use, planning, multi-agent collaboration, memory management, learning/adaptation, MCP, goal setting, exception handling, HITL, RAG, A2A, resource optimization, reasoning techniques, guardrails, evaluation, prioritization, exploration/discovery). All rules and guidance are grounded in the PDF "Agentic Design Patterns" (482 pages).
Product manager that decomposes requirements into actionable tasks with priorities and dependencies
Complete ElevenLabs AI audio platform: text-to-speech (TTS), speech-to-text (STT/Scribe), voice cloning, voice design, sound effects, music generation, dubbing, voice changer, voice isolator, and conversational voice agents. Use when working with audio generation, voice synthesis, transcription, audio processing, or building voice-enabled applications. Triggers: generate speech, clone voice, transcribe audio, create sound effects, compose music, dub video, change voice, isolate vocals, build voice agent, ElevenLabs API/SDK/CLI/MCP.