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RunwareRunware/runware-skills/skills/edit-video/SKILL.md

edit-video

Skill8 starsChanged 5 months agoMITView on GitHub

Restyle or relight an existing video, changing the whole frame's look while the motion carries. Use when the user says "restyle this clip", "make this footage look like winter", "turn this into a cartoon", "relight this scene", "give the whole video a new look", or "edit this video without redoing it". This is a global look change across the frame. To swap one specific element such as an actor, a product, or a garment while everything else stays put, use replace-in-video. For aspect ratio, use reframe-video. For resolution, use video-upscale. For sound, use add-audio-to-video.

13 other projects use a version of this.

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Projects with it also use cut-mistakes, cut-silences and 10 more.

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  • nateherkaiSkill

    cut-mistakes

    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.

    Also in 5 projects that use this

  • nateherkaiSkill

    cut-silences

    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.

    Also in 5 projects that use this

  • NexumAI-onlineSkill

    short-form-edit

    Convertí una grabación hablada en un reel, YouTube Short o anuncio corto terminado, con apertura que genere curiosidad, resolución respaldada por el contenido, cortes narrativos, gráficos sincronizados, B-roll en movimiento, subtítulos, música sutil y efectos. Para videos largos usá edit-video; para quitar sólo pausas, cut-silences.

    Also in 4 projects that use this

  • Google CloudSkill

    video-storytelling

    Cinematic video ad storytelling expertise. Covers 3-act narrative structure, emotional arcs, camera motion, scene transitions, and voiceover pacing for 10-second commercial video ads using Gemini Omni. Load this skill when generating video ads or storylines.

    Also in 5 projects that use this

  • ConardLiSkill

    motion-showreel

    用代码制作图形、文字或界面动画视频,输出 MP4 和可编辑源码,最长 20 分钟。适用于动效作品集、产品片、UI 动效、动态排版、Logo 片头、生成艺术与讲解视频;支持独立选择 BGM/音效来源、用户口播,以及用用户提供的口播稿通过 TTS 合成语音。不用于实拍制作、写实人物生成或一般视频剪辑。

    Also in 4 projects that use this

  • chriswesttSkill

    make-a-video

    Beginner-friendly end-to-end video creator for HyperFrames. Use when the user says "make a video", "create a video", "new video", "build a video", "video from scratch", "I want to make a video", "help me create a video", or when someone who's never used HyperFrames before arrives with a concept, script, or rough idea and wants a finished MP4. Interviews the user in one pass, then builds the full video with mandatory preview and visual-verification gates.

    Also in 4 projects that use this

  • +2 more from nateherkai

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 0 are distinctive, and 2 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.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run taskType: videoInference asynchronously: the task returns a taskUUID, then poll getResponse until terminal.

    line 38
  2. Very specific:

    Read the result from videoURL.

    line 39

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Edit video

Take a clip the user already has and change it, without regenerating from scratch. There are two distinct jobs, and picking the wrong one wastes a run: a whole-frame transform that reimagines the entire shot in a new look while the original motion and timing carry through, or a surgical edit that changes one named region and holds the rest of the clip pixel-stable. This is video-to-video, so every run is async.

Inputs to collect

  • The source clip. A public URL or the UUID of a previous generation. (Ask only if none provided.)
  • What change the user wants, and how far it should travel: a full restyle of the whole frame, or one specific localized edit (a color, a region, an environment, a wardrobe piece).
  • What must stay the same. For a surgical edit this is load-bearing: the framing, the cuts, the lighting, the subject, the parts not being touched.
  • Optional: a restyled or edited reference frame to pin the exact target look (anchoring).

Models

  • Whole-frame transform / restyle: Luma Ray 3.2 (luma:ray@3.2). Pass inputs.video + a prompt describing the target look, and the model re-renders the entire frame guided by the source. The original motion carries through, but faces and backgrounds are reimagined along with the style, not held. Use it for bold restyles where the performance is the throughline and the new look is the point.
  • Surgical / localized edit: Runway Aleph 2.0 (runway:aleph@2.0). Pass inputs.video + a positivePrompt naming one change. It returns the same clip with that change applied and everything else preserved: framing, cuts, lighting math, the regions you did not name. Use it for a paint color, an environment swap, a wardrobe change, or a grade.
  • Confirm both are live and inspect each schema via runware-models + runware-run before calling. Never hardcode a stale choice.

Pick correctly, this is the whole skill. Ask one question: should the whole frame be reimagined, or should only one named thing change while the rest stays identical? "Make this clip look like an anime" is a transform (Luma). "Change the red car to blue" is surgical (Aleph). When the source frame and the result differ everywhere, that is Luma. When they differ only inside one region, that is Aleph. To swap a specific character or object for a different one, that is its own job, see replace-in-video.

Route with: Change <what> while keeping <what stays>. A long "keeping" list against a small change is surgical (Aleph). A short or empty "keeping" list because the look should travel everywhere is a transform (Luma).

Workflow

  1. Resolve the chosen model's schema (runware-run) and confirm the input field names before calling.
  2. Provide the source as inputs.video (URL or prior-generation UUID). For Aleph, plan around the 2 to 30 second, up-to-1080p source limits.
  3. Run taskType: videoInference asynchronously: the task returns a taskUUID, then poll getResponse until terminal. Do not block a sync call on a minutes-long edit.
  4. Read the result from videoURL.
  5. Review against the quality bar below and retry with a tuned strength (Luma) or a tighter preserve-clause (Aleph) if it drifts.

See references/examples.md for worked async requests: a whole-frame Luma restyle and a surgical Aleph edit, by prompt and by anchor.

Technique

  • Transform (Luma Ray 3.2): describe the look, let the motion carry. Name the target style and trust the source for motion and composition. Do not expect faces or backgrounds to stay untouched, the model rebuilds the whole frame. settings.edit.strength is the preserve-versus-reinterpret dial across three bands (adhere close to source, flex moderate liberties, reimagine loose guidance), each with three levels. Start low. For people, the face control biases toward a recognizable face, though a heavy transform still reinterprets it. settings.edit.autoControls: true derives the conditioning from the source on the first pass and cannot be combined with strength or manual controls. Editing keeps the source aspect ratio, so changing format is a separate reframe step.
  • Surgical (Aleph 2.0): name only what changes. The clip already holds the framing, cuts, lighting, subject, and motion. Describing any of those tells the model they are fair game and the part you wanted preserved drifts. Lead with a transformation verb the model honors cleanly (change, replace, swap, add, remove, restyle, relight), name the target attribute, then end with a short clause pinning the rest in place ("keep the chrome, the road, and the lighting exactly as in the source"). That closing clause is what stops a color change from also rebuilding the road. Art-direction phrasing beats caption phrasing.
  • Anchor when words are not enough. Both models accept inputs.frameImages: a reference frame pinned to a position in the clip via frame (a name like first/last or a zero-based index) or, on Aleph, a timestamp. Pull a still from the source, edit it externally to the exact target look while keeping the source framing, then send it back. The model treats the anchor as the target appearance at that moment and carries it through. This is the way to lock a brand identity, exact typography, or a custom pattern that a prompt only approximates.
  • Aleph carries one edit across cuts. A multi-shot source reel gets a single edit propagated through every cut, as long as the subject reads as continuous. Sharp identity jumps between shots can break propagation, edit those as separate clips.

Parameters that matter

  • inputs.video - the source, a URL or a prior-generation UUID. Aleph requires 2 to 30 seconds at up to 1080p, output preserves the input aspect ratio.
  • settings.edit.strength (Luma) - bands adhere_1 … reimagine_3. Lower preserves shape and motion, higher reworks the subject. Start in adhere/flex.
  • settings.edit.controls / autoControls (Luma) - per-signal conditioning (poseStrength, depthBlur, face, …), or let autoControls derive it. autoControls excludes strength and manual controls.
  • positivePrompt (Aleph) - required, capped at 1000 characters. Name one change, then pin the rest.
  • inputs.frameImages (both) - up to 5 anchors on Aleph; pin with frame or timestamp. Match the anchor's framing to its pinned moment.
  • Confirm exact field names against the live schema (runware-run); never guess.

Quality bar

  • The right tool was chosen: a whole-frame restyle went to Luma, a one-region change went to Aleph. A surgical request that rebuilt the unnamed parts of the frame is a wrong-model failure, not a prompt tweak.
  • For a surgical edit, only the named region changed. Framing, cuts, lighting, and untouched elements are pixel-stable against the source.
  • For a transform, the original motion and timing carry through and the new look is coherent across the clip, not flickering frame to frame.
  • The job was run async and read from videoURL, not blocked on a sync call. Retry drift with a tuned strength or a tighter preserve-clause before returning.

Related skills

runware-run, runware-models, runware-prompting; replace-in-video (swap a specific character or object for a different one), reframe-video (change the clip's aspect ratio or format).

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