936 skills · sorted by relevance
Summarize articles, YouTube videos, podcasts, and local files, or extract available text and transcripts. Choose the summary length to suit the task and use transcript extraction to inspect video content when available.
Turn audio and video into text with Whisper, including Japanese and other supported languages. This skill covers transcription, English translation, timestamped subtitles, model selection, and batch processing, with guidance on hardware needs and recognition limitations.
Develop C++ bots that join existing Zoom meetings from Linux servers without a graphical interface. Follow guidance for recording raw audio and video, feeding transcription or AI workflows, and handling authentication, recording permissions, and Docker audio setup.
Helps developers build systems that receive live Zoom audio, video, transcripts, chat, and screen sharing. Covers SDK setup, persistent WebSocket connections, media selection, and troubleshooting for recording, transcription, and meeting assistants.
Turn sales call transcripts or notes into a customer follow-up draft, an internal team summary, and proposed customer record updates. Capture decisions, concerns, and commitments, with source references supporting the suggested changes.
Summarize customer interview transcripts into a consistent Markdown document. Capture what customers want to accomplish, their current solutions, satisfaction and problems, notable findings, and follow-up actions with dates and owners when available.
Turn meeting transcripts, rough notes, or long meeting chats into structured notes with decisions, open questions, risks, and action items. Include task owners and deadlines, with an optional short summary for Slack or email.
Turn recorded audio and video into text or timestamped subtitles with Whisper. This skill covers transcription across 99 languages, language detection, translation into English, batch processing, and model selection for available computing resources.
Fetch raw Fireflies.ai meeting transcripts. Use only when the user explicitly invokes /fireflies-transcript; for YouTube, use youtube-transcript.
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Use when a video/audio task needs OpenChatCut transcription, captions, subtitles, subtitle styling, transcript search, transcript readiness checks, or enabling captions, including local or attached videos where the user asks to add captions/subtitles, transcribe, create bilingual subtitles, clean talking-head speech, remove filler words, or trim pauses.
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Automatically fetch YouTube video transcripts, generate structured summaries, and send full transcripts to messaging platforms. Detects YouTube URLs and provides metadata, key insights, and downloadable transcripts.
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Ultra-fast speech transcription using iFLYTEK Speed Transcription API. Transcribe audio files (WAV/PCM/MP3) up to 5 hours in ~20 seconds per hour. Supports Chinese, English, and 202+ Chinese dialects with automatic language detection. Use when user asks to transcribe audio files, convert speech to text, or mentions "speed transcription" or "极速转写".
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AssemblyAI is a hosted speech-to-text API that transcribes audio and video files or live streams and adds speaker labels, sentiment, entity detection, PII redaction and LLM analysis of the transcript. Use when a user asks to transcribe a recording, label who said what, analyze call sentiment, redact personal data, stream live transcription, or summarize and question a transcript with LLM Gateway (the replacement for LeMUR).
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Deterministic workflow to find and export full podcast transcripts as cleaned TXT files from YouTube URLs, episode webpages (including Xiaoyuzhou), Apple Podcasts title search, X/Twitter links, direct audio URLs, or plain episode titles. Use when users ask for 逐字稿/文字版/transcript/txt and want minimal trial-and-error.
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Transcribe local MP4/M4A/MP3/WAV/WEBM audio or video with ffmpeg and Whisper, then optionally produce diarized transcripts, customer-facing meeting minutes, action items, and PPT-ready summaries. Use when: 文字起こし, transcription, transcribe mp4, meeting transcript, mp4から文字起こし, 録画から議事録, 顧客向け議事録, 話者分離, diarization, whisper CLI, ffmpeg.
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Fetch transcripts from YouTube videos for summarization, analysis, or reference. Accepts video ID or full URL. No API key required. Triggers: YouTube transcript, video transcript, get subtitles, what did they say in the video, summarize YouTube, extract video text, caption from video.
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Generate strategic-consultant-grade meeting minutes from transcripts or notes in Japanese OR English (matching the source language), then run a self-review loop (max 3 iterations) that checks for internal contradictions, action-item omissions, speaker-name errors, and date/day-of-week mistakes before reporting completion. Use this skill whenever the user asks to draft meeting minutes, summarize a transcript, or document a meeting discussion — including Japanese-language transcripts (議事録 / 会議メモ / 文字起こし) and English-language transcripts.
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Turns one meeting transcript or recap into a DRAFT action-items document (decisions, owned and dated action items with verbatim source quotes, open questions), a task list ready for the user to enter into their task tracker, and one DRAFT follow-up email per action owner, all returned in the chat for the user to store, create or send. Use when the user shares, names or points to a meeting transcript or recap and asks to "pull the action items from this transcript", "who owns what after today's call", "draft follow-up emails to each owner" or "turn this recap into tasks". Do not use for full minutes, use meeting-minutes-writer instead; a brief before a meeting is meeting-prep-onepager. Drafts for human review; never approves, authorises or signs off.
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Pull an earnings call (or investor-event) transcript from Quartr (FMP fallback), extract qualitative signal (management commentary deltas, hedging shifts, Q&A tone), and produce a thesis-delta-first Research note. Use when user says "transcript", "pull earnings call", "transcript diff", or "ingest [TICKER] earnings".
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Pull an earnings call transcript from Financial Modeling Prep, extract qualitative signal (management commentary deltas, hedging shifts, Q&A tone), and produce a thesis-delta-first Research note. Use when user says "transcript", "pull earnings call", "transcript diff", or "ingest [TICKER] earnings".
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Automatically fetch YouTube transcripts, generate structured summaries, and send full transcripts to messaging platforms. Use when a request includes YouTube URLs and needs metadata, key insights, or downloadable transcripts.
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Search and retrieve notes, transcripts, and panels from a local Granola archive. Check whether data is current, refresh it when needed, and use read-only SQL, a database query language, for exact counts and rankings.
Summarize articles, YouTube videos, podcasts, PDFs, and local files to understand their main points. Choose the summary length or extract source content, including available YouTube transcripts, for closer reading and further processing.
Search local notes, documents, and meeting transcripts using keywords and meaning. Combine both methods and use local AI models to reorder results by relevance, then retrieve full documents or selected passages without cloud processing.