「recordings」の検索結果

Make a short product film (website hero loop, landing section, launch film, feature walkthrough, store-listing promo, social cut, illustrated story film) in which the product appears as its own real UI, drawn frame by frame from an HTML timeline, rendered with Playwright and cut with ffmpeg. Four routes: licensed footage cut against cinematic product beats, product beats only, a pointer-driven walkthrough with captions or text cards (plain or kinetic), or a cut-paper collage in which an illustrated cast tells a story over real UI captured from the code with fictional data. Use when asked for a product film, hero video, promo or demo video, launch film, explainer, walkthrough video, paper or collage film, or to recut one. Not for plain screen recordings or voice-over walkthroughs; laying a supplied music track under a finished cut is in scope.

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Transcribe audio files locally with Interpreter's builtin-transcribe tool server. Use when a user asks to transcribe speech from recordings without cloud transcription or API keys.

日本語の概要は準備中です。原文の説明を表示しています。

Drive running Unity Editor from shell to verify compiles, playmode, scenes, screenshots. Use when editing C# scripts, scenes, or assets in a Unity project and needing to: (1) check compilation succeeds, (2) read console errors, (3) enter/exit Play mode, (4) capture screenshots or frame recordings, (5) select objects or aim the Scene camera, (6) query editor window layout. Injects a file-polling command bridge (UnityRemote.cs) — prefer this over batchmode (fights the Library lock) or GUI automation.

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Review Zoom meetings, calls, recordings, and transcripts. Use to catch up on missed calls, summarize decisions, and extract action items and owners; also work with Team Chat, Canvas, Tasks, Whiteboard, Hub, and Revenue Accelerator through Zoom's official MCP servers.

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Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.

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Native video analysis using Google Gemini API. Upload and analyze video files — describe scenes, extract text/UI, answer questions about content, transcribe speech, identify objects and actions. Use when: (1) User sends a video file and wants it analyzed, (2) Video summarization or description needed, (3) Extracting text, UI elements, or information from screen recordings, (4) Answering questions about video content, (5) Comparing multiple videos, (6) Analyzing tutorials, demos, or walkthroughs.

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Automated cell behavior analysis from microscopy or XR lab recordings. Classifies cell motion phenotypes (migration, proliferation, apoptosis, division, quiescence), computes population-level quantitative metrics (growth rate, migration velocity, directionality index), and emits structured JSON for downstream reporting, plotting, or ELN integration.

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

日本語の概要は準備中です。原文の説明を表示しています。

Capture baseline evidence from a live website URL: screenshots, scroll states, hover/click behavior, parallax, timers, and transition recordings. Use when reference artifacts are needed before implementation or comparison; not to build or diagnose a clone.

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Use when Amazon Ads optimization analysis, recommendations, approval packets, demos, recordings, or public artifacts must preserve exact source KPIs while masking account/profile/project names, products, ASINs, SKUs, campaigns, ad groups, keywords, search terms, targets, placements, filenames, URLs, and source-derived identifiers. Produces masked approval packets only; it must not directly mutate Amazon Ads.

日本語の概要は準備中です。原文の説明を表示しています。

[Testing] Use when generating, updating, or maintaining E2E tests from recordings, specs, or code changes.

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

日本語の概要は準備中です。原文の説明を表示しています。

Query PostHog product analytics via REST API — event analytics, HogQL SQL queries, feature flags, experiments, session recordings, insights, persons, cohorts. Use when the user wants to answer an analytics question, toggle/inspect a flag, or pull event data programmatically without opening the PostHog UI or installing the PostHog MCP.

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Query the user's local and synced-device data via the screenpipe REST API at localhost:3030 — recordings, audio, UI, meetings, connected services, and memory. Use for screen activity, other-device or cross-device history, productivity, media export, connections, durable memory, or discovering and automating saved workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Google Meet skill for creating meeting spaces, reviewing conference records, and managing participants and recordings via the gws CLI.

日本語の概要は準備中です。原文の説明を表示しています。

Cut raw takes into an approved, rendered edit. Use at the cut stage with recordings in raw/, or when the user says "cut the takes", "make the cutplan", "render the preview", or "render the final".

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Daily Co — daily.co video and audio API platform management for real-time video calls, rooms, recordings, and usage analytics. Use when monitoring active rooms, analyzing meeting quality, reviewing usage and billing, managing room configurations, or troubleshooting Daily.co video sessions.

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Transform transcripts, conversations, or raw notes into shareable content — either multiple social posts OR a single long-form article. Learns style from user's published content. Handles transcripts of any length (tested up to 5500+ lines / 90+ min). Use when user: (1) provides transcript/conversation/recording and wants social content, (2) asks to "turn recording/notes into posts", (3) mentions generating content from recordings/notes, (4) needs multiple publishable pieces from single source, (5) asks to write an article from a transcript — e.g. "write an article/long-form", "organize into an article", "write up this session", "turn this talk into a blog post", "deep dive". Social mode outputs 2-15 ready-to-publish pieces. Article mode outputs a structured long-form piece (3000-10000+ chars) written section-by-section.

日本語の概要は準備中です。原文の説明を表示しています。

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.

日本語の概要は準備中です。原文の説明を表示しています。

Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.

日本語の概要は準備中です。原文の説明を表示しています。

Focused Signals scout for PostHog projects running Replay Vision scanners — the standing LLM probes that watch session recordings and write `$recording_observed` events. Watches two promises: that enabled scanners are actually observing (throughput / success-rate cliffs, exhausted quota — a silent watch gap), and that what the scanners see in aggregate gets surfaced (a monitor's `yes`-rate or a scorer's score stepping away from its own baseline, a classifier tag or a recurring summarizer theme concentrating across many sessions). It is the agentic pull complement to the per-session push path: scanners with `emits_signals` already emit one signal per session into this same inbox, so this scout never repeats them — it adds the cross-session shape the per-session probe can't see. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

日本語の概要は準備中です。原文の説明を表示しています。