'transcript' 검색 결과

Share the current coding session transcript with the Convex team, with explicit consent, for an AI review that identifies unclear setup instructions, tooling failures, and successful patterns to help improve the quickstart system.

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• Reviewing where an agent got stuck during setup
• Reporting tooling failures in a coding session
• Sharing successful setup patterns with the Convex team

Retrieve video subtitles and turn them into a clean paragraph, with optional timestamps and bracketed cues. Download video, audio, or subtitle files, inspect available formats, and choose a language or specific download format.

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• Turn video subtitles into readable text
• Save a video or its audio locally
• Download subtitles in a selected language

Preserve the context of long Claude Code sessions across compaction, which shortens conversation history. Create a restore map linking decisions, files, and next steps, then use ranked readings and targeted transcript lookups to rebuild working context.

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• Preparing a restore map before conversation compaction
• Rebuilding working context after /compact
• Preserving decision history across long-running work

Query gnomAD for variant frequencies, gene constraint measures, and effects on gene transcripts. Get concise Markdown summaries from focused requests, with options to return machine-readable JSON or save the full response to a file.

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• Checking the frequency of a specific genetic variant
• Retrieving gene constraint measures
• Looking up variant effects on gene transcripts

Turn articles, transcripts, or notes into a structured talk summary. Identify whether the material centers on practical experience or ideas, then extract its narrative, themes, sourced metrics, and gaps to guide further preparation.

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• Starting a talk from an article or notes
• Assessing source material before committing to a talk
• Organizing measurable results with their sources

Investigate unexpected Claude Code output by matching a session’s local transcript with production router logs. Identify the serving model and trace response conversion code to explain empty blocks, tool output, or other rendering symptoms.

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• Investigate unexpected output in a specific session
• Examine an empty thinking block
• Match displayed content to the serving model and provider

Shape Markdown notes, fragments, or transcripts into a separate article through a collaborative drafting session. Choose an opening, establish what readers already know, and develop each paragraph or block in an order that introduces concepts before relying on them.

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• Turning scattered notes into an article
• Developing an article from a transcript
• Comparing openings to choose an angle

Analyze interviews, focus groups, and open-ended survey responses using Braun and Clarke's six-phase framework. Label meaningful passages, develop and review themes, and produce an academic Word report with an annotated map showing theme relationships.

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• Identifying themes across interview transcripts
• Analyzing open-ended survey responses
• Choosing an approach before coding qualitative data

Use when the user wants to summarize, analyze, or repurpose transcripts from TikTok, Instagram, YouTube, Facebook, X/Twitter, LinkedIn, Rumble, or Reddit video posts. Extracts hooks, claims, quotes, content atoms, themes, and reusable scripts.

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Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

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Work with the user's meetings through the Vexa MCP tools — send a bot to a call, follow the transcript while it runs, and write meetings into their notes (Obsidian, Notion, plain markdown) with speakers and action items. Use whenever the user mentions a meeting, a call, a transcript, meeting notes, or asks what was said.

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Analyze and triage AssemblyAI REST, transcript, Streaming v3, webhook, and LLM Gateway failures without leaking customer content. Use when an integration errors or stalls. Trigger with "AssemblyAI error" or "failed transcript".

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Analyze and operate a production AssemblyAI pre-recorded pipeline with explicit models, Speech Understanding, callbacks, and retention controls. Use when running asynchronous transcription. Trigger with "AssemblyAI async transcription" or "pre-recorded pipeline".

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Fetch transcripts from YouTube videos for summarization and analysis.

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Turn one long asset - a YouTube video, podcast, newsletter, blog post, transcript or client call - into a week of LinkedIn posts. Use when the user says "repurpose this", "turn this into posts", "I have a video/newsletter/ transcript", or pastes a long piece of content and wants it on LinkedIn.

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Extract subtitles and transcripts from Bilibili and YouTube videos. Use when the user wants to get subtitles from B站 (Bilibili) or YouTube, extract Chinese/Japanese video transcripts, watch member-only Bilibili content, or perform Q&A on video content. Supports dual-platform subtitle extraction with yt-dlp.

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Turn a raw recording's transcript into an edit decision list - dead air, filler cues and retakes, with timecodes. Use for "edit this", "cut the dead space", "tighten this video", "I rambled", or any request to shorten footage from a transcript.

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Agent 1 of the video editing pipeline. Removes silences and dead air from a talking-head recording. Use when asked to cut silences, trim pauses, remove dead air / gaps, or tighten the pacing of a raw video, given a word-level transcript. Produces an edit list (EDL), a re-timed transcript for downstream agents, and optionally the cut video via ffmpeg. Does NOT cut mistakes, repeats, or false starts — that is the cut-mistakes agent.

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Extract subtitles/transcripts from YouTube videos. Triggers: "youtube transcript", "extract subtitles", "video captions", "视频字幕", "字幕提取", "YouTube转文字", "提取字幕".

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Analyze a product walkthrough, bug report video, Loom, or ScreenPal using Minutes transcription plus visual review. Use when the user wants a recorded demo or bug clip turned into a durable brief with transcript, key frames, issues, and next steps.

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Agent 1 of the video editing pipeline. Removes silences and dead air from a talking-head recording. Use when asked to cut silences, trim pauses, remove dead air / gaps, or tighten the pacing of a raw video, given a word-level transcript. Produces an edit list (EDL), a re-timed transcript for downstream agents, and optionally the cut video via ffmpeg. Does NOT cut mistakes, repeats, or false starts — that is the cut-mistakes agent.

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Reads, searches and exports local Claude Code and Kimi CLI history without resuming work: timelines, verbatim user input, keyword or fuzzy recall, file recovery from transcripts, and which session ran a given command in a known time window. Use when the user asks what was said, wants a session ID or original context, needs proof of what a session contained, or needs past-session runtime evidence about commands, tool calls and hook runs — query this index instead of raw-scanning transcript files. Not for Codex (use read-codex-history); with no platform or several named, start at local-conversation-history.

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Fetch existing YouTube transcripts/subtitles or archive spoken video content as text, and download YouTube videos/audio or HLS streams (m3u8) with yt-dlp and ffmpeg. Use for transcript/subtitle retrieval, text-first video archiving, video/audio downloads, protected streams with authentication headers, and download failures including nsig, 403 or browser-cookie issues.

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Create a framing document from conversation transcripts. Use when the user has transcripts (VTT, call notes, etc.) and wants to produce a frame that captures the problem worth solving and why it was chosen over alternatives.

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