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Found 6,569 Skills
MCP server for real-time Three.js scene inspection, material editing, shader debugging, and performance monitoring from AI agents
SurgeGraph is the Answer Engine Optimization (AEO) platform that tracks AI citations, scores pages for citation readiness, and one-click fixes the gaps — now every workflow runs from the terminal or any agent. Trigger phrases: `what changed in SurgeGraph this week`, `AI Visibility for my project`, `which prompts lost AI citations`, `publish gap articles from a topic research`, `what knowledge libraries actually show up in citations`, `use surgegraph`, `run surgegraph`.
This skill should be used when the user asks to "create an agent", "make an agent", "write an agent", "build a subagent", "add an agent to a plugin", "design an autonomous agent", "generate an agent file", "write a system prompt for an agent", "what frontmatter does an agent need", "create a specialized agent". Not for skills or commands — use create-skill.
This skill should be used when the user asks to "repair an agent", "audit an agent", "fix my agent", "review agent quality", "check if my agent is well-written", "diagnose agent problems", "what's wrong with this agent", "improve this agent", or "what's wrong with this agent file". Not for skills — use repair-skill.
Elastic ML anomaly detection skill — investigation/RCA, score explanation, job operations (create, datafeed, start/stop, results), and troubleshooting (missing docs, memory limits, datafeed health, lifecycle). Operates against Kibana Agent Builder MCP tools (`ad_*`) on `.ml-anomalies-*`, `.ml-config`, `.ml-notifications-*`, `.ml-annotations-*`. Use when answering "what broke?"/"which entity?"/RCA, "why is score high/low?"/renormalization, "datafeed stopped"/"memory limit", or any request to set up or configure an ML anomaly detection job.
The meta skill. Turn any raw feature into a properly-skilled, tested, resolvable unit of agent capability. Cross-modal eval is the recommended Phase 3 quality gate: 3 frontier models from different providers critique the output, you iterate to quality, THEN write tests that lock in the proven-good behavior.
Run provider-agnostic live voice conversations with VAD, silence boundaries, wake-word gating, STT, and TTS through the AgentOS speech runtime.
Install and configure ktx, the self-improving context layer that teaches AI agents to query data warehouses accurately with approved metrics, semantic layer, and business knowledge.
Generate social media covers and assets for AGENCY Community events, meetups, and YouTube recordings. Use when creating event covers, YouTube thumbnails, or social posts for the AGENCY Community.
Security scanner and health check for your AI agent skills tree. Identifies dead skills, missing documentation, and unsafe shell execution paths.
The agentmemory plugin hooks that capture observations automatically across the agent session lifecycle. Use when explaining how memory gets captured without manual saves, when debugging missing observations, or when tuning what gets recorded.
Declared architecture snapshot for one Agentforce agent: planner, topics, actions, flows, Apex, prompt templates, and NGA plugins. Renders a human-readable architecture document and Mermaid invocation graph from design-time metadata (not runtime audit rows). TRIGGER when user asks to describe, diagram, inventory, audit, document, or diff (e.g. v3 vs v5) the architecture / action tree / topic structure / tool inventory of a specific agent by agent API name in a specific org. DO NOT TRIGGER for runtime session traces, conversation transcripts, generation timings, or gateway audit chains — this skill reads design-time metadata only (use investigating-agentforce-d360 for session traces).