video-editor
Skill1.2k starsChanged 16 days agoMITView on GitHub
Conversation-driven video editing on the ComfyTV canvas — rough cuts, silence removal, pacing passes, montages, trims, concat assemblies, speed changes, color grades, and subtitle burns over footage the user already has. Use when the user explicitly invokes $video-editor or asks to edit footage, cut out dead air or filler, tighten pacing, assemble clips into a sequence, grade a video, or burn subtitles. Reads the video through composite timeline views instead of frame-dumping; always confirms the cut strategy in plain English before touching anything.
19 other projects use a version of this.
Adopted by
Most recently taken up by
- orage-developers/skills-editortheir own version, first seen Nov 8, 2026
- Jrkesari/skillstheir own version, first seen Nov 8, 2026
- weibo-job/guagua-animation-skillstheir own version, first seen Nov 8, 2026
- fralapo/awesome-agent-skillstheir own version, first seen Nov 7, 2026
- humzabuilds/claude-skillstheir own version, first seen Oct 20, 2026
- nelsonelagunar/obs-ai-workflowtheir own version, first seen Oct 15, 2026
Other versions19 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 19
- ckorhonen/claude-skills★ 17same name
- coopersimson96/ai-content-system★ 17same name
- EverythingAI-Pro/ai-video-editor★ 16same name
- Isaac-Flath/agent-starter-skills★ 8same name
- darker2016/WorkbuddySkillGroups4DSH★ 6same name
- EmersonBraun/skills★ 4same name
- kevinaimonster/skill-hub★ 4same name
- tyler-berggren/tb-claude-kit★ 2same name
- weibo-job/guagua-animation-skills★ 2same name
- fralapo/awesome-agent-skills★ 1same name
9 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository2 other files it gives its agents.
- brainstormSkill
- h3-cinematic-directorSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 0 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 12 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 21
Never scan a video by pulling frames one by one.
- Very specific: line 34
If a transcript helps (dialogue-heavy footage) and a speech-to-text workflow is available, add a ComfyTV.SubtitleGenStage, run it, and read …
- Very specific: line 57
Self-eval before presenting: After the final render, run media_timeline on the RENDERED output at every cut boundary (±1.5s): look for …
- Very specific: line 65
The canvas is the project file: Keep the graph tidy (arrange_canvas) and show the user what you built (canvas_focus).
“Common” is measured: kept by at least 6 in 10 of the 12 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Video Editor
Purpose
Edit existing footage by conversation. The material is the user's — takes, renders, downloads, generated clips. The job is editorial: what to keep, where to cut, how to pace, how it should look. Everything is built as stages on the user's canvas, so every decision stays visible and adjustable after you leave.
Invoke with $video-editor or infer from an editing request. Do not widen the
task into generating new footage unless asked — generation is the Director
stage's job, editing is yours.
Core principle: read the video, don't watch it
Never scan a video by pulling frames one by one. Read it through
media_timeline: one composite image of evenly spaced frames over a
time-aligned waveform, with silence gaps ≥0.35s shaded AND returned as data
(silences). The silence spans are your cut candidates before you have looked
at a single frame.
media_probefirst — duration, fps, resolution, has_audio.media_timelineover the whole clip for the first read; again over narrow ranges (±1.5s) at decision points — ambiguous pauses, boundary checks.media_frame+view_imageonly when you need one frame at full attention.- Audio is primary, visuals follow: cut candidates come from silence gaps and speech boundaries; drill into visuals only to confirm.
If a transcript helps (dialogue-heavy footage) and a speech-to-text workflow
is available, add a ComfyTV.SubtitleGenStage, run it, and read the SRT it
returns. Convert its cues to {text, start, end} objects and pass them as
words to media_timeline to get a labeled timeline. SRT cues are
phrase-level, not word-level — pad cuts more generously when relying on them.
Hard rules
- Strategy confirmation before execution. Describe the plan in plain English — what gets cut, kept, reordered, graded — and wait for the user's OK before building or running anything.
- Never cut mid-speech. Snap every cut edge to a silence gap from
media_timeline. Gaps ≥400ms are the cleanest; 150–400ms need a visual check; below 150ms is unsafe. - Pad every cut edge 30–200ms into the silence. Tighter for montage energy, looser for cinematic pacing.
- Subtitles burn LAST.
SubtitleStagegoes after every concat, speed, and FX stage in the chain — anything composited after it will cover the captions. - Preview cheap before rendering expensive. Iterate looks with
fx_preview(one FX stage, ~1.2s window) until the frame is right, THEN set the stage and render. Render one boundary clip to verify a doubtful cut before building the whole chain. - Self-eval before presenting. After the final render, run
media_timelineon the RENDERED output at every cut boundary (±1.5s): look for visual jumps, waveform spikes (audio pops), and captions hidden by later compositing. Fix and re-render at most 3 times, then flag what remains instead of looping. - Don't re-run what didn't change. Stages keep their outputs; Director clips re-render only when edited. Re-running an unchanged chain wastes the user's GPU time.
- The canvas is the project file. Keep the graph tidy (
arrange_canvas) and show the user what you built (canvas_focus). Never leave orphaned stages behind.
Tool map
Reading:
media_probe— metadata; always first.media_timeline— filmstrip + waveform + silence data; the primary read.media_frame+view_image— one frame, actually looked at.media_waveform— audio-only files.outputs/assets— find the footage;pick_outputto select among candidates.
Cutting and assembly (wire with add_stage, set_stage, connect_stages,
then run_stage / wait_stage):
ComfyTV.VideoClipStage— keep one range (start_s,end_s). One kept segment = one clip stage.ComfyTV.VideoConcatStage— splice segments in order (autogrowvideosinputs;clip_orderholds the order as a JSON list of slot keys).ComfyTV.VideoSplitStage— one cut point, two outputs.ComfyTV.VideoSpeedStage— speed ramps;ComfyTV.VideoCropStage— reframe;ComfyTV.VideoVolumeStage— gain and audio fades.ComfyTV.SubtitleGenStage— speech-to-text workflow → SRT text out.ComfyTV.SubtitleStage— burn SRT/VTT (subswidget or wired text input).
Look development:
fx_preview→ FX stages (VideoColorStage,VideoCurvesStage,CDLStage, … — seestage_catalog) →FXChainStagerenders the whole chain in one transcode. Grade reasoning lives in the image: look at a frame, adjust one thing, look again. Test skin tones before going aggressive.
Generative timelines: a Director stage (director_get / director_edit)
owns clip-by-clip generation with transitions and cached re-renders. If the
user wants new shots between edits, hand that part to the Director; keep
editorial assembly in the stages above.
The process
- Inventory.
media_probe+ full-rangemedia_timelineon every source. Note lengths, silence patterns, visual character. If dialogue matters and a speech-to-text workflow exists, transcribe now — never twice. - Converse. Say what you see in plain English. Ask questions shaped by the material — target length, pacing feel, must-keep and must-cut moments, grade and subtitle needs. No fixed checklist; the right questions differ every time.
- Propose strategy. 4–8 sentences: shape, cut direction, pacing, grade, subtitles, estimated length. Wait for confirmation (hard rule 1).
- Execute. Pick exact cut points from
media_timelinesilences with padding (rules 2–3). Build clip stages → concat → speed/FX → subtitles last. Run and wait. - Self-eval (rule 6), then present with
canvas_focuson the result. - Iterate. Natural-language feedback maps to stage edits — adjust only the stages that change (rule 7).
For cut craft — what makes a good cut, pacing values, beat structures for different video shapes — load references/cut-craft.md.
Taste
Everything not in the hard rules is a taste call, and taste calls are yours to make from what the material wants: hold on laughs and reactions past the punchline, leave air between speakers (400–600ms; less for energy, more for cinema), never reason audio and video independently — every cut must work on both tracks. Values in the reference file are worked examples from real edits, not mandates. Invent freely when the material calls for something the tools support.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

