Loading...
Loading...
Found 15,310 Skills
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management", or needs ADK (Agent Development Kit) Python API patterns and code examples. Part of the Google ADK skills suite. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, and state management. Do NOT use for creating new projects (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).
This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets. Covers deployment workflows, service accounts, rollback, and production infrastructure. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for API code patterns (use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold).
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini Enterprise", "publish to Gemini Enterprise", or needs guidance on the agents-cli publish gemini-enterprise command. Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
This skill should be used when the user wants to "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle and coding guidelines. Entrypoint for building ADK agents. Always active — provides the full workflow (scaffold, build, evaluate, deploy, publish, observe), code preservation rules, model selection guidance, and troubleshooting steps for ADK or any agent development.
This skill should be used when the user wants to "run an evaluation", "evaluate my ADK agent", "write an evalset", "debug eval scores", "compare eval results", or needs guidance on ADK (Agent Development Kit) evaluation methodology and the eval-fix loop. Covers eval metrics, evalset schema, LLM-as-judge, tool trajectory scoring, and common failure causes. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for API code patterns (use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the Google ADK (Agent Development Kit) skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).
Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.
Run any model on RunComfy from the command line. The `runcomfy` CLI is one binary, one auth, hundreds of model endpoints — image generation, image edit, video generation, image-to-video, lip-sync, face swap, video edit, inpainting, outpainting, extend, ControlNet, relight, upscale, LoRA training and more. Submit a request, poll for status, download the output. This skill teaches the agent how to install, authenticate, discover model schemas, invoke models, stream / poll / no-wait, script in JSON output mode, and handle errors. Triggers on "runcomfy cli", "install runcomfy", "runcomfy login", "runcomfy run", "runcomfy whoami", "runcomfy api", or any explicit ask to call a RunComfy model from a script or terminal. Sibling skills (ai-image-generation, ai-video-generation, image-edit, video-edit, face-swap, lipsync, image-to-video, image-inpainting, image-outpainting, video-extend, controlnet-pose, relight) all dispatch through this CLI.
Video outpainting on RunComfy via the `runcomfy` CLI — extend the spatial canvas of a video, change aspect ratio (9:16 vertical to 16:9 horizontal or vice versa), add environment beyond the original frame while preserving the central action. Routes prompt-shaped spatial extension through Wan 2-7 edit-video and points the agent at dedicated ComfyUI outpaint workflows when seam quality matters for hero delivery. Triggers on "video outpaint", "video outpainting", "extend video canvas", "expand video frame", "uncrop video", "aspect ratio change", "vertical to horizontal video", "16:9 from 9:16", "TikTok to YouTube", or any explicit ask to extend a video spatially beyond its original frame.
Feishu Video Conference: Allow bots to join/leave ongoing meetings on behalf of the current user, and read real-time events during the meeting (participant join/leave, speaking, chatting, screen sharing, etc.). 1. When users provide a 9-digit meeting number and request to join or leave on their behalf, use +meeting-join / +meeting-leave — this will generate actual join/leave records. 2. During a meeting, when users want to know in-meeting dynamics such as "who joined", "who left", "who is speaking", "is someone sharing their screen", the bot can use +meeting-events to read the event timeline after joining the meeting. 3. Typical scenarios: Meeting participant bot, in-meeting assistant, proxy attendance, proxy participation. Prerequisite: The bot can only read events of meetings that it has joined and are still ongoing; to query the participant list, minutes, or transcript of an ended meeting, please use the lark-vc skill.