Loading...
Loading...
Found 23 Skills
Takes meeting transcripts, extracts action items with owners and deadlines, detects implicit commitments, generates structured meeting summaries, and outputs task files compatible with Linear, GitHub Issues, and other project management tools.
Access and process Granola meeting notes and transcripts via the granola CLI (MCP-backed). Use when pulling meeting data, analyzing transcripts, backfilling meetings, or any task involving Granola meeting content.
Convert normalized timed transcript data into subtitle artifacts such as SRT and VTT. Use this when a stable normalized transcript JSON already exists and the main job is subtitle chunking, timing normalization, and export packaging.
Fetch and display the full transcript from a Loom video URL. Use when the user wants to get or read a Loom transcript.
Index YouTube channel videos and transcripts for semantic search. Use when user says "index YouTube", "add YouTube channel", "update video index", or "index transcripts". Works with solograph MCP (if available) or standalone via yt-dlp.
Turn meeting transcripts or rough notes into crisp summaries with decisions, risks, and owner-tagged action items; use for Zoom/Meet/Teams transcripts, call notes, or long meeting chats to generate share-ready outputs.
Vendor-neutral skill to extract decisions and action items from a meeting transcript and produce a decision log plus an action register.
Fetch meetings, transcripts, summaries, and action items from Fathom API. Use when user asks to get Fathom recordings, sync meeting transcripts, or fetch recent calls.
Agent 2 of the video editing pipeline. Finds and removes spoken mistakes — stutters, repeated words, false starts, and retakes (re-recorded lines) — from a talking-head recording. Use after cut-silences, when asked to cut mistakes, remove stutters / repeats / filler restarts, clean up flubs, or keep the best take. Works review-gated: it proposes every cut with context and a reason for approval, then renders only the approved cuts via ffmpeg. Requires a word-level transcript.
【Long-content clipping】Long-content clipping. Cut transcripts of courses, live retrospectives, interviews, and private-domain internal training into short-video plans that can be posted individually—the opening, development, and ending can come from three locations far apart in the transcript, assembled with jump cuts into a complete narrative. Only output the plan; don't add a single word. Use when the user says “help me clip,” “how many clips can this live stream make,” “here’s the transcript, clip it,” “course clipping,” or “find a few segments I can post.” | Produced by Xiao Ye
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.