Agno 是一个高性能 Python 框架，用于大规模构建、运行和管理智能体软件。它提供三层架构——框架、运行时和控制平面——使开发者能够在大约 20 行代码内将智能体原型转化为生产 API。
Agno 是一个高性能的 Python 框架，旨在帮助开发者大规模构建、运行和管理智能体软件。它采用三层架构（框架、运行时、控制平面），使得从智能体原型到生产 API 的转换仅需大约 20 行代码。该技能支持人类审批机制，可暂停运行等待用户确认，并阻止需要管理员审批的工具。它支持在任何运行容器的云平台上部署，包括 Docker、Railway、AWS、GCP 等。Agno 的核心优势在于让开发者完全掌控自己的智能体栈，包括数据、上下文、工具、权限、记忆和人工审查循环，同时通过精美的 UI 进行管理。该技能适用于 Agent Skill Exchange 平台，原始代码托管在 GitHub，文档提取自上游官方仓库。
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/agno-multi-modal-agent-runtime-platformAgno 是一个高性能 Python 框架，用于大规模构建、运行和管理智能体软件。它提供三层架构——框架、运行时和控制平面——使开发者能够在大约 20 行代码内将智能体原型转化为生产 API。
来自上游的要求和注意事项：
基本使用或入门说明：
构建、运行和管理智能体平台。
将其作为生产服务运行，支持追踪、调度和 RBAC。
Agno 允许您拥有自己的智能体栈。保持对数据、上下文、工具、权限、记忆和人工审查循环的控制。在您自己的云中运行您的平台，并通过精美的 UI 进行管理。
提取自上游文档：https://raw.githubusercontent.com/agno-agi/agno/HEAD/README.md
This repo contains 20 individual skills — each has its own dedicated page.
Builds citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.
Exposes Advanced Custom Fields data through the WordPress REST API using register_rest_field and acf_format_value. Handles repeater fields, flexible content layouts, and gallery fields with proper serialization.
An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field workflows.
Converts Advanced Custom Fields field groups into native Gutenberg blocks using the ACF Block API v2 and @wordpress/scripts build pipeline. Maps ACF repeaters, groups, and flexible content to InnerBlocks and block attributes with server-side rendering via acf_register_block_type().
Activepieces is an open-source, self-hostable workflow automation platform with 200+ integrations. It provides a visual builder for creating automated workflows and exposes all its connectors as MCP servers for AI agent use.
ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.
act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.
Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.
Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.
Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.
Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.
Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.
Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.
Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.
Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.
Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.
Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.
Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.
Calls Adobe Firefly
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.