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Found 12,388 Skills
Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
Use Agent Pulse to inspect AI agent activity, token usage, tool calls, model usage, cost, budgets, forecasts, reports, local log sources, health checks, and MCP tools. Use when the user asks to check how much AI agents have been used, what sessions ran, what models cost, whether spending is high, generate Agent Pulse reports, diagnose Agent Pulse setup, or expose Agent Pulse data to other agents.
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
Convex backend specialist. Use this agent for any code inside a `convex/` directory — function definitions, schemas, indexes, queries, mutations, actions, HTTP endpoints, cron jobs, file storage, auth wiring, and component installation. Knows the object-form function syntax, validator patterns, resource limits, and component ecosystem that generic Claude routinely gets wrong.
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.
Add a capability to the CURRENT Convex app — consults the served Convex capability catalog for always-current procedures (billing, crons, auth, agent, search, …); falls back to built-in hosting or @convex-dev component search. TRIGGER when the user runs /add, or asks to add hosting/publishing or any backend capability to an existing Convex app.
Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.
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.
Add an AI agent / RAG backend (@convex-dev/agent) to the Convex app.
Onboard an agent to Bright Data. Use when a coding agent first encounters Bright Data — for live web work (search, scrape, structured data), for wiring Bright Data into product code, for installing the agent skill bundle, or for getting an API key. One install command sets up the CLI, agent skills, and authentication. Routes the reader to the right path: live tools, app integration, MCP, auth-only, or direct REST without any install.
阿里云百炼托管 Agent 声明式基础设施入口：用户要创建agent、初始化 agents.yaml、校验或预览 agent 配置变更、 创建/更新/销毁百炼托管 Agent、和托管 agent 对话、查会话事件历史、导入或取消跟踪远端资源时使用 `bl managed-agent`。以 agents.yaml 为唯一事实源做 IaC：init 建脚手架、validate 离线校验、plan 预览 diff、 apply / destroy 变更远端资源且必须带 `--yes`，务必先 plan 给用户看 diff 再让其确认。 反触发：调用已上线的百炼应用/智能体走 bailian-app-call 或 `bl app`；宿主 agent 自身的记忆、技能、 子代理不走本 skill；生图生视频走 bailian-gen。 官方安装：`npx skills add modelstudioai/cli --all -g`（与共享协议 bailian-protocol 同装）。