AssemblyAI 即時通話智能分析 是做什麼的？
透過 WebSocket 將 Twilio Media Streams 的音訊串流至 AssemblyAI 即時語音辨識，提取帶有說話者標記及逐字時間戳記的逐字稿，並對完成通話段落觸發實體辨識與情感分析，最終將結果推送至 HubSpot 或 Salesforce 的聯絡人記錄。
安裝
來自上游的需求與注意事項：
- Python SDK
基本使用或快速入門備註：
-
概述
-
使用 AI 編碼代理構建
-
模型
透過 WebSocket 將 Twilio Media Streams 的音訊串流至 AssemblyAI 即時語音辨識，提取帶有說話者標記及逐字時間戳記的逐字稿，並對完成通話段落觸發實體辨識與情感分析，最終將結果推送至 HubSpot 或 Salesforce 的聯絡人記錄。
AssemblyAI 即時通話智能分析技能實現了 Twilio 通話音訊與 AssemblyAI 語音智能分析的即時整合。它透過 WebSocket 串流音訊至 AssemblyAI 進行即時語音辨識，不僅產生帶有說話者標記（speaker diarization）的逐字稿，還能精確到每個字的時間戳記。每個通話段落完成後，技能會自動調用 AssemblyAI 的 LeMUR 功能進行實體偵測與情感分析，從而捕捉通話中的關鍵資訊與情緒趨勢。最後，這些結構化數據會經由 REST API 寫入 HubSpot 或 Salesforce 的聯絡人記錄，讓客服、銷售或支援團隊能即時獲得通話洞察。本技能支援主流開發平台（如 Claude Code、Cursor、Codex 等），並使用 Python SDK 進行整合，適合需要自動化通話分析與客戶關係管理同步的場景。
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/assemblyai-realtime-call-intelligence透過 WebSocket 將 Twilio Media Streams 的音訊串流至 AssemblyAI 即時語音辨識，提取帶有說話者標記及逐字時間戳記的逐字稿，並對完成通話段落觸發實體辨識與情感分析，最終將結果推送至 HubSpot 或 Salesforce 的聯絡人記錄。
來自上游的需求與注意事項：
基本使用或快速入門備註：
概述
使用 AI 編碼代理構建
模型
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.