Results for “meeting notes”

Turn a process walkthrough -- meeting transcript, screen-recording transcript, rough notes, or a folder of scattered how-to docs -- into a clean standard operating procedure: numbered steps, roles, decision points, exceptions, and a consistent template across your whole SOP library.

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Build a quarterly business review from a client folder -- reports, usage exports, support tickets, meeting notes, emails. Extracts delivered value with receipts, surfaces risks before the client does, and drafts the QBR narrative plus expansion asks. For agencies, consultancies, and CS teams.

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会議テキストやメモから構造化された議事録を自動生成するスキル。 「議事録をまとめて」「会議メモを整理して」「アクション項目を抽出して」等のリクエストで発動。

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把凌亂的文件（會議逐字稿、多場會議混在一起的檔案、實驗／數據報告、論文、財報）變成可直接上台的設計感簡報的工作流。 Use this skill whenever the user wants to turn a document, meeting notes, transcript, report, spreadsheet, or raw data into slides / a presentation / a deck — 包括他們說「做成簡報」「整理成投影片」「幫我做一份簡報」「把這份報告變簡報」 「turn this into a presentation / slides / a deck」，即使沒有明說步驟。 也適用於「只有主題沒有素材」（如「幫我做一份 AI 發展趨勢的簡報」）——會先做主題研究再進入流程。 也適用於跨 session 銜接（「繼續做 xxx 的簡報」「接上次」）——會定位進度再銜接。 它會先清點內容並把敏感資料（姓名、薪資、競業條款、個資）攔進備援區、停下來等使用者確認範圍， 再把「有設計感」翻成具體色碼與版型規格、生成單一 HTML 簡報， 並對任何圖表用原始數據重算統計值、抓出原文寫錯的數字。 Also use it whenever the user needs figures or charts from a report recomputed from the source data rather than trusted blindly. 也支援 Keynote Magic Move 式的 Morph Transition 轉場（使用者說「Magic Move」「Morph」「物件飛過去的轉場」時）。

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Use when choosing between engines or models for an agent pipeline and the answer must come from measurement on your own data, not from marketing pages: speech recognition for meeting recordings, the model that turns a transcript into notes, the critic model that checks it. Runs every variant in an isolated container, measures time, cost per hour of input (USD and RUB, with price source and date) and quality (WER/CER and course terms for ASR; code checks plus a judge of a different model for LLM steps), writes results.json/csv and one static analytics page. Triggers on "бенчмарк", "сравни движки", "сколько стоит час записи", "какую модель взять для пайплайна", "benchmark the pipeline", "compare ASR engines".

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Capture, organize, and retrieve notes efficiently using structured formats, tagging, and file management for meetings, ideas, research, and daily logs. Use when the user requests note taking or provides relevant inputs for this workflow.

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Produce full-length audiobooks and long-form narration with generative voice tools. Use when the task is to turn a manuscript or long text into hours of spoken audio: preparing the manuscript for narration (front/back matter, footnotes, tables, dialogue), casting a single narrator or full cast, controlling pronunciation and voice consistency across a whole book, running a proofing/QC listen, meeting a retailer's technical delivery specs (RMS, peak, noise floor, room tone, chapterized files, metadata), and choosing a distribution route under each platform's current AI-narration policy. Not for short TTS clips, single-line voiceover, podcast production, or captioning existing video.

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Verify meeting notes are fully processed. Args: <path>, [dates], all, pending [dates] [--step=X]. Shows which wrap steps are complete or missing.

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Evidence-first team memory operator for turning consented Feishu, Slack, email, meeting notes, and project documents into decision logs, ownership maps, unresolved-question queues, retrospectives, and onboarding packets. Use when a team says decisions are lost in chat, onboarding is slow, or a project needs a searchable memory layer.

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Evidence-first expert knowledge handoff skill. Use when a founder, senior engineer, salesperson, support lead, consultant, or other domain expert is leaving, changing roles, or needs their judgment made reusable. It turns consented documents, chat, meeting notes, interviews, and explicit facts into a traceable handoff package. Trigger on requests such as: "capture this expert's judgment", "prepare a departure handoff", "make an onboarding mentor", "extract the decision rules", or "把专家经验交接下来".

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Use when the user dumps a batch of inputs at once — a pile of emails, a backlog of Slack/Teams messages, a list of asks, meeting action items, a notes brain-dump — and needs it sorted into action. Classifies each item, assigns owner + next step + priority, and flags which need a full /structure brief or a /decide call. Trigger on "/triage", "triage this", "process my inbox", "sort these asks", "clear my backlog", "what do I do with all this".

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Non-interactive content-production toolkit: mine quotable moments from podcast RSS feeds and meeting notes, discover clip-worthy moments in video transcripts, repurpose long-form source into platform-native drafts (X, LinkedIn, YouTube Shorts, newsletter), and batch-score/gate those drafts before publish. Use when asked to "mine quotes from this podcast", "find clips in this video", "repurpose this into a thread / LinkedIn post / Short", "turn this transcript into posts", "extract viral moments", or "gate this batch of drafts". Runs Python scripts end to end. For interactive expert-panel scoring of a single artifact see content-ops.

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Morning startup workflow for daily notes, yesterday summary, agenda, status comments, meeting sections, and daily branch setup. Use when invoked as `$work-start-day` or when the user asks to start the work day.

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Map existing materials into a first knowledge record, or investigate a subject's history in depth. Use whenever the user asks to map, survey, go through, reconstruct or investigate what already exists - folders of documents, decision records, meeting notes, emails, exports, code - or wants a starting record built from existing materials, even when the word 'record' is never said: consult this before listing or reading the files yourself, because a map has an agreed scope, a protocol and a report. Also, once, at a suitable moment, to offer the starting choices where a workspace has no record and the work is clearly ongoing - never on a greeting. Learning while working needs no map. Requests come in any language.

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Format and publish rich Notion documents with structured sections, code blocks, tables, callouts, quotes, mermaid diagrams, and emojis. Use when the user asks to organize, write, or save content to Notion (e.g., "notion에 정리해줘", "notion에 저장해줘"), or when invoked with /notion-format. Detects content type (tech-doc, meeting-notes, analysis, tutorial, bug-report) and applies the appropriate formatting template automatically.

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Turns plain-language requests (emails, chat messages, form submissions, meeting asks, voicemail or call notes) into one intake record per request (what is asked, who asks and for whom, urgency as evidenced, category, suggested owner, missing information with draft clarifying questions) and a triage table sorted for the operations lead to act on. Use when the user asks to "log these requests", "triage this pile of asks", "turn this message into an intake record", "who should own this request", "what is missing before we can start" or "build today's intake list". Do not use for customer support tickets, use ticket-triage-pack instead; for clearing a personal mailbox by reply bucket, use inbox-triage. Drafts for human review; never approves, authorises or signs off.

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Turns one decision discussion (meeting transcript, chat thread, email chain or notes) into a DRAFT one-page decision memo: the decision as stated, status, options considered, evidence cited, dissent recorded verbatim, owner, effective date and review date, with UNKNOWN for anything the discussion did not settle. Use when the user asks to "write up the decision", "record what we decided", "capture the decision from this thread", "draft the decision memo" or "add this to the decision log". Do not use for full minutes or action items, use transcript-to-actions instead; for a technical design decision, use architecture-decision-record; for a paper seeking a decision not yet taken, use board-paper-skeleton. Drafts for human review; never approves, authorises or signs off.

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Turns reported data problems (messages, tickets, meeting notes, complaints) into one DRAFT issue log: one row per issue with the symptom as reported, dataset and fields named, reproduction steps, affected reports, first seen date, reporters, a suggested owner, and blank severity, root cause and status cells for the owner. Never asserts a root cause, severity or fix. Use when the user asks to "log these data issues", "turn these complaints about the numbers into an issue list", "build the data quality backlog", "which reports are hit by this data problem" or "write up the reproduction steps for this data bug". Do not use for exploring or profiling a dataset, use dataset-insight-pack instead; for an IT incident write-up, use incident-postmortem-drafter; for tracking fix actions once assigned, use corrective-action-tracker. Drafts for human review; never approves, authorises or signs off.

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Join a Google Meet call, transcribe live captions, optionally speak in realtime, and do the followup work afterwards. Use when the user asks the agent to sit in on a meeting, take notes, summarize, respond in-call, or action items from it.

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Search personal knowledge bases, notes, docs, and meeting transcripts locally using qmd — a hybrid retrieval engine with BM25, vector search, and LLM reranking. Supports CLI and MCP integration.

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