“transcript”的搜索结果

Help QM organization admins inspect settings, stored memory, conversations, files, and operational records across the organization. It also supports confirmed configuration changes and external user management, while keeping admin grant changes in the dashboard.

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• Check whether the requester is an organization admin
• Inspect or update organization and channel settings
• Investigate agent behavior using transcripts and captured prompts

Find statements, decisions, and commitments in Circleback meeting records. Search by people, company, tags, or dates, then use notes and transcripts to distinguish discussion from agreement and identify the meeting behind each answer.

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• Checking what was agreed with a customer
• Finding who promised a deadline
• Looking up exact wording in a meeting

Find what people said, decided, or promised in Granola meetings. The skill narrows meetings by date and participants, checks notes before transcripts, distinguishes decisions from discussion, and supports each finding with its meeting title and date.

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• Checking decisions from last week's customer call
• Verifying the exact wording of a commitment
• Reviewing customer feedback across multiple meetings

Turn long articles, reports, papers, and transcripts into summaries at the reader’s preferred depth. Lead with the main conclusion, preserve essential figures and qualifications, and extract action items when the source supports them.

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• Summarizing an article in one sentence
• Extracting key points from reports or papers
• Organizing decisions and tasks from transcripts

Turn rough meeting notes or a transcript into a structured recap with decisions, assigned tasks, stated deadlines, and open questions. Include a brief summary and flag missing or uncertain details so readers can identify the next steps.

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• Turn rough meeting notes into a shareable recap
• Extract tasks with owners and stated deadlines
• Track unresolved questions after a discussion

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

Investigate product demand through Reddit, social posts, transcripts, and comments. Get sourced customer pain points, buying signals, existing alternatives, and objections, plus messaging angles and product tests grounded in the language people actually use.

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• Investigating demand for a new product idea
• Finding recurring problems in a niche
• Collecting buyer language and purchase objections

Adapt an article, script, or transcript into posts for multiple social platforms. Extract the central message, supporting points, quotes, and data, then rewrite each version to suit its platform and suggest a publishing sequence.

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• Adapt a long article into posts for multiple platforms
• Turn a video script into image posts and spoken scripts
• Create short posts from a livestream or podcast transcript

Keep lengthy agent transcripts out of the main conversation by using synchronous Task calls that return summaries. This skill sets a specific execution rule intended to preserve separate agent contexts and avoid triggering conversation compaction.

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• Receiving a summary after an agent finishes its task
• Reviewing workflows that retrieve results with TaskOutput
• Keeping full agent transcripts out of the main conversation

Coordinate background agents using system progress reminders while continuing other work. Read their output files after completion signals, avoiding repeated status checks and full transcripts that consume tokens and crowd the main conversation.

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• Continuing other work while a background agent runs
• Reducing repeated checks for agent output
• Reading completed results without loading full transcripts

Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.

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• Keeping long agent transcripts out of the main conversation
• Passing research and plans between agents through files
• Checking for stalled background agents

Search local session histories across Codex, Claude Code, OpenCode, and other coding agents. Find earlier requests, inspect transcripts and child sessions, and reconstruct past work using recorded evidence, with filters for dates, projects, platforms, and models.

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• Finding work done a few days ago
• Checking whether a migration was already completed
• Reviewing tasks delegated to child agents

Turn speech from audio or video recordings into text using OpenAI. Save transcripts as text or JSON, with optional speaker labels and reference recordings to help identify known speakers in meetings or interviews.

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• Transcribe recorded meetings
• Label speakers in interviews
• Extract spoken text from audio or video

Convert documents, spreadsheets, images, and audio into structured Markdown for AI processing. Extract tables, recognize text in images, transcribe audio, and batch convert files using command-line tools or Python.

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• Convert PDF papers into Markdown
• Extract Excel tables for analysis
• Recognize text in scanned documents

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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