[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6BXZF3DJD8DBAJB7961HDF6":3,"skill-same:01M6BXZF3DJD8DBAJB7961HDF6":106},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":54,"ownerHtmlUrl":55,"ownerBlogUrl":12,"ownerDescription":56,"updatedAt":57,"install":58,"resources":71},"01M6BXZF3DJD8DBAJB7961HDF6","explainer-storyboard",null,"Turn a confirmed product or feature brief into a shootable 30–120 second explainer storyboard with a consistent entity roster. Use for the beat structure of an explanatory product video, not workflows, pipelines, or finished renders. A narrated explainer whose shots are timed to the voiceover also loads script-video for the script, voice and timing.","nodetool-ai\u002Fnodetool","nodetool-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F164873569?v=4","01M6BXPFDW36K9K1MR8ZH63HG2","nodetool.ai","01M6BXPFJ893XM219GQN60B0WK",630,"AGPL-3.0","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fexplainer-storyboard\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"explainer","explainer storyboard","storyboard","structure","second","shots","for","script","with","loads","timing","roster","feature","workflows","voiceover","use","voice","Video","brief","product","2026-11-10 10:12:30",false,"---\nname: explainer-storyboard\ndescription: Turn a confirmed product or feature brief into a shootable 30–120 second explainer storyboard with a consistent entity roster. Use for the beat structure of an explanatory product video, not workflows, pipelines, or finished renders. A narrated explainer whose shots are timed to the voiceover also loads script-video for the script, voice and timing.\n---\n\n# Explainer Storyboard → Storyboard Agent\n\nCreate a complete, shootable explainer beat sheet as a NodeTool storyboard. Work directly through the storyboard and entity capability modules. Do not build a workflow or run a pipeline. Do not render stills, clips, or assemble a timeline unless the user asks.\n\nThis skill is the explainer's structure. When the voiceover should time the shots, load `script-video` as well: write the VO from this beat sheet into a script, voice it, and let the linked board take each shot's length from its takes. `ad-story-loops` orders the reveals so the aha is set up before it lands.\n\n## Truthful brief\n\nCollect these facts before creating a board: product or feature, brand and traits, category, audience, core problem, shift, 2–4 concrete mechanism steps, proof assets, CTA, runtime (30, 60, 90, or 120 seconds), platform, tone, mandatory content, and forbidden claims. The core problem, shift, and mechanism are required. Never invent a capability, integration, metric, screen, or customer. Write `[CLIENT INPUT NEEDED]` wherever proof is not confirmed.\n\n## Resolve entities before beats\n\nEvery recurring person, location, product UI, device, metaphor object, brand mark, and visual style is an entity. Start with `list_entities`; reuse user-provided references and existing entities before generating anything. A real product screenshot is a `prop` reference and must never be regenerated.\n\nResolve a style entity first. Generate only missing references, applying that style before generating each other entity. A typical 60-second explainer has 4–7 entities: style, persona, optional location, product UI prop, and metaphor prop. Label generated UI as a mock.\n\nUse `create_entity` with a dense visual descriptor. The descriptor specifies the exact recurring appearance: character features and wardrobe; location materials and lighting; UI layout, palette, typography, and content boundaries; metaphor geometry and material; or style medium, palette, lighting, and lens. An entity id is the asset id supplied to `create_entity`.\n\n## Teaching arc\n\nCompute timecodes from the selected runtime, rounded to 0.5 seconds. Use this arc:\n\n| Beat | Runtime share |\n| --- | --- |\n| Problem | 0–15% |\n| Stakes | 15–25% |\n| Shift | 25–40% |\n| Mechanism 1 | 40–55% |\n| Mechanism 2 | 55–68% |\n| Outcome \u002F proof | 68–82% |\n| CTA | 82–93% |\n| Sign-off | 93–100% |\n\nFor 30 seconds, combine problem and stakes and use one mechanism beat. For 90–120 seconds, use at most three mechanism beats. Use one concept and one literal metaphor. Put the visual aha at the shift-to-mechanism boundary and leave a deliberate half-beat of silence after it. Voice-over must be at most `runtime × 2.2` words.\n\n## Deliverables\n\nProduce, in order: three concept directions with a recommendation, the full beat sheet, and an entity roster with id, kind, descriptor summary, and referenced beats. Each direction states its entry problem, metaphor, aha, fit, risk, and referenced entities.\n\nFor every beat include timecode, teaching job, framing, visual, action, visible entities, verbatim VO, on-screen text of five words or fewer, exact UI\u002Fdemo input and output or `NONE`, sound, music, transition, and why it teaches. Mechanism beats must show the real UI or a labelled mock. Brand marks wait until the shift. Use verbs in VO and nouns on screen. The sign-off echoes the opening problem.\n\n## Persist the board\n\nCreate the storyboard with `create_storyboard({ name, brief, style, aspect_ratio })`. Use `board.storyboard_id`. Put the complete brief, chosen direction, and entity roster into `brief` so the project can be reconstructed later. The exact call shapes and return fields — entity id equals the asset id you passed in, the fifteen `edit_storyboard` ops, what `set_board` accepts, what each prompt receives — are in `storyboard-core` § Tool contract; every board skill builds against that one section.\n\nAttach roster ids with `edit_storyboard({ storyboard_id, ops: [{ op: \"set_board\", entity_ids }] })` (`set_entities` is only an alias for `set_board`). Resolve the render models in the same op: `find_model` for `text_to_image` and `image_to_video`, each result's `.ref` on `image_model` \u002F `video_model`, and each result's `prompting_skill` loaded before the shot text is written — the still model reads the shot `action` with the camera framing, angle and lens, the scene lighting and the board style appended.\n\nAdd one shot per beat with `edit_storyboard` and an `add_shot` op. The dense `action` field names the teaching job, visible entity names in brackets, on-screen text, and UI demonstration. The render attaches a persona or prop entity to a shot only when its name appears in that shot's text (style and location always apply), so every visible entity must be named in `action` or `motion`, or listed on the shot's own `entity_ids`. On-screen text in `action` is a note for the cut: it goes on as a text clip after assembly (`caption-titles`), not into the render prompt.\n\nStop after the planned board unless the user explicitly requests rendering or a cut. Report the directions, chosen board, and entity roster.\n\n## Render (only on request)\n\nStills first with `render_storyboard_stills` — they cost less than clips, and you look at every one with `view_image` asking what is wrong, then `score_image_adherence` against the shot text. A persona or UI mock that drifts is fixed at the entity (descriptor or reference), then every shot using it re-renders; a shot that fails on composition is fixed in its `action`. Clips with `render_storyboard_clips`; a clip wrong where its still was right is one `revise_storyboard_clip`. Then `assemble_storyboard_timeline`.\n\n## When the board becomes motion\n\nWhen a cut is asked for, `timeline-edit-ops` carries the timeline op contract and `motion-graphics` the build loop, which routes to the craft skill for the job: `video-audio-continuity` for whether the beats render as one clip or under a narration track, `caption-titles` for the on-screen text and callouts this beat sheet already specifies, `frame-composition` for where a UI mock sits and whether it survives 9:16, `motion-direction` to hold one motion language across the mechanism beats, and `beat-sync-editing` when the cut has to sit on a music bed. The half-beat of silence after the aha is a hold, not a gap — keep it in the cut.\n","# Explainer Storyboard → Storyboard Agent\n\nCreate a complete, shootable explainer beat sheet as a NodeTool storyboard. Work directly through the storyboard and entity capability modules. Do not build a workflow or run a pipeline. Do not render stills, clips, or assemble a timeline unless the user asks.\n\nThis skill is the explainer's structure. When the voiceover should time the shots, load `script-video` as well: write the VO from this beat sheet into a script, voice it, and let the linked board take each shot's length from its takes. `ad-story-loops` orders the reveals so the aha is set up before it lands.\n\n## Truthful brief\n\nCollect these facts before creating a board: product or feature, brand and traits, category, audience, core problem, shift, 2–4 concrete mechanism steps, proof assets, CTA, runtime (30, 60, 90, or 120 seconds), platform, tone, mandatory content, and forbidden claims. The core problem, shift, and mechanism are required. Never invent a capability, integration, metric, screen, or customer. Write `[CLIENT INPUT NEEDED]` wherever proof is not confirmed.\n\n## Resolve entities before beats\n\nEvery recurring person, location, product UI, device, metaphor object, brand mark, and visual style is an entity. Start with `list_entities`; reuse user-provided references and existing entities before generating anything. A real product screenshot is a `prop` reference and must never be regenerated.\n\nResolve a style entity first. Generate only missing references, applying that style before generating each other entity. A typical 60-second explainer has 4–7 entities: style, persona, optional location, product UI prop, and metaphor prop. Label generated UI as a mock.\n\nUse `create_entity` with a dense visual descriptor. The descriptor specifies the exact recurring appearance: character features and wardrobe; location materials and lighting; UI layout, palette, typography, and content boundaries; metaphor geometry and material; or style medium, palette, lighting, and lens. An entity id is the asset id supplied to `create_entity`.\n\n## Teaching arc\n\nCompute timecodes from the selected runtime, rounded to 0.5 seconds. Use this arc:\n\n| Beat | Runtime share |\n| --- | --- |\n| Problem | 0–15% |\n| Stakes | 15–25% |\n| Shift | 25–40% |\n| Mechanism 1 | 40–55% |\n| Mechanism 2 | 55–68% |\n| Outcome \u002F proof | 68–82% |\n| CTA | 82–93% |\n| Sign-off | 93–100% |\n\nFor 30 seconds, combine problem and stakes and use one mechanism beat. For 90–120 seconds, use at most three mechanism beats. Use one concept and one literal metaphor. Put the visual aha at the shift-to-mechanism boundary and leave a deliberate half-beat of silence after it. Voice-over must be at most `runtime × 2.2` words.\n\n## Deliverables\n\nProduce, in order: three concept directions with a recommendation, the full beat sheet, and an entity roster with id, kind, descriptor summary, and referenced beats. Each direction states its entry problem, metaphor, aha, fit, risk, and referenced entities.\n\nFor every beat include timecode, teaching job, framing, visual, action, visible entities, verbatim VO, on-screen text of five words or fewer, exact UI\u002Fdemo input and output or `NONE`, sound, music, transition, and why it teaches. Mechanism beats must show the real UI or a labelled mock. Brand marks wait until the shift. Use verbs in VO and nouns on screen. The sign-off echoes the opening problem.\n\n## Persist the board\n\nCreate the storyboard with `create_storyboard({ name, brief, style, aspect_ratio })`. Use `board.storyboard_id`. Put the complete brief, chosen direction, and entity roster into `brief` so the project can be reconstructed later. The exact call shapes and return fields — entity id equals the asset id you passed in, the fifteen `edit_storyboard` ops, what `set_board` accepts, what each prompt receives — are in `storyboard-core` § Tool contract; every board skill builds against that one section.\n\nAttach roster ids with `edit_storyboard({ storyboard_id, ops: [{ op: \"set_board\", entity_ids }] })` (`set_entities` is only an alias for `set_board`). Resolve the render models in the same op: `find_model` for `text_to_image` and `image_to_video`, each result's `.ref` on `image_model` \u002F `video_model`, and each result's `prompting_skill` loaded before the shot text is written — the still model reads the shot `action` with the camera framing, angle and lens, the scene lighting and the board style appended.\n\nAdd one shot per beat with `edit_storyboard` and an `add_shot` op. The dense `action` field names the teaching job, visible entity names in brackets, on-screen text, and UI demonstration. The render attaches a persona or prop entity to a shot only when its name appears in that shot's text (style and location always apply), so every visible entity must be named in `action` or `motion`, or listed on the shot's own `entity_ids`. On-screen text in `action` is a note for the cut: it goes on as a text clip after assembly (`caption-titles`), not into the render prompt.\n\nStop after the planned board unless the user explicitly requests rendering or a cut. Report the directions, chosen board, and entity roster.\n\n## Render (only on request)\n\nStills first with `render_storyboard_stills` — they cost less than clips, and you look at every one with `view_image` asking what is wrong, then `score_image_adherence` against the shot text. A persona or UI mock that drifts is fixed at the entity (descriptor or reference), then every shot using it re-renders; a shot that fails on composition is fixed in its `action`. Clips with `render_storyboard_clips`; a clip wrong where its still was right is one `revise_storyboard_clip`. Then `assemble_storyboard_timeline`.\n\n## When the board becomes motion\n\nWhen a cut is asked for, `timeline-edit-ops` carries the timeline op contract and `motion-graphics` the build loop, which routes to the craft skill for the job: `video-audio-continuity` for whether the beats render as one clip or under a narration track, `caption-titles` for the on-screen text and callouts this beat sheet already specifies, `frame-composition` for where a UI mock sits and whether it survives 9:16, `motion-direction` to hold one motion language across the mechanism beats, and `beat-sync-editing` when the cut has to sit on a music bed. The half-beat of silence after the aha is a hold, not a gap — keep it in the cut.\n",{"name":5,"description":7},"main","c7226baa82daca42a19a5855c116544f97aa8bac","packages\u002Fsystem-skills\u002Fexplainer-storyboard",90,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool","https:\u002F\u002Fnodetool.ai\u002F","https:\u002F\u002Fgithub.com\u002Fnodetool-ai","No-code AI development","2026-11-13 03:21:10",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add nodetool-ai\u002Fnodetool --skill explainer-storyboard",{"tool":64,"command":65},"bunx","bunx skills add nodetool-ai\u002Fnodetool --skill explainer-storyboard",{"tool":67,"command":68},"pnpm","pnpm dlx skills add nodetool-ai\u002Fnodetool --skill explainer-storyboard","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fexplainer-storyboard\u002FSKILL.md",true,[72,78,82,86,90,94,98,102],{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"references\u002Fai-access-and-models.md","REFERENCE","参考文档",2795,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Fai-access-and-models.md",{"path":79,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":80,"sourceHtmlUrl":81},"references\u002Fapps-and-mcps.md",1614,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Fapps-and-mcps.md",{"path":83,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Ffirst-things-to-try.md",2751,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Ffirst-things-to-try.md",{"path":87,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Fhow-dc-differs-from-other-tools.md",1580,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Fhow-dc-differs-from-other-tools.md",{"path":91,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fproduct-mental-model.md",2745,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Fproduct-mental-model.md",{"path":95,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":96,"sourceHtmlUrl":97},"references\u002Fskills.md",2231,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Fskills.md",{"path":99,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":100,"sourceHtmlUrl":101},"references\u002Ftroubleshooting-and-common-confusions.md",2948,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Ftroubleshooting-and-common-confusions.md",{"path":103,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":104,"sourceHtmlUrl":105},"references\u002Fuse-cases-by-goal.md",5792,"https:\u002F\u002Fgithub.com\u002FTrollz1004\u002FANTIGRAVITY\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fdesktop-commander-guide\u002Freferences\u002Fuse-cases-by-goal.md",[107,139,166,180,194,219],{"skillNo":108,"name":109,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":111,"categories":112,"keywords":121,"publishedAt":44},"01M6BY4D93R0Q9400ZHJ04DXP1","nodetool","Use the NodeTool MCP server to build, validate, run, and debug visual AI workflows, and to work with assets, collections, and jobs. Use when the user mentions NodeTool or asks for a workflow graph, a node, or a media generation run on their NodeTool server.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fplugins\u002Fchatgpt\u002Fnodetool\u002Fskills\u002Fnodetool\u002FSKILL.md",[113,116],{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":117,"categoryName":118,"taxonomyType":119,"taxonomyTypeDesc":120},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[109,122,123,124,37,125,126,127,128,129,130,131,132,133,39,134,135,136,137,32,30,138],"MCP","mcp server","workflow","validate","debug","run","graph","server","Media","assets","work","node","visual","generation","collections","media generation","when",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":146,"publishedAt":44},"01M6BY4AEB05ZPBRVD078ATR2H","wan-2-6-prompting","Prompt Alibaba's Wan 2.6 video — text-to-video with a global style line plus timing-bracketed shots, and image-to-video that describes only what changes over time. Covers the shot-mode switch per provider, the prompt budget, negative prompts, motion intensity wording, audio input and prompt expansion. Use whenever the model id names a Wan 2.6 video route (alibaba\u002Fwan-2.6\u002Ftext-to-video, alibaba\u002Fwan-2.6\u002Fimage-to-video, wan-video\u002Fwan-2.6-t2v, wan-video\u002Fwan-2.6-i2v, wan-video\u002Fwan2.6-i2v-flash) on generate_video, animate_image or a TextToVideo node. Not for Wan 2.5 or 2.7, or the Wan 2.6 image routes.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fwan-2-6-prompting\u002FSKILL.md",[145],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[147,148,149,150,151,41,152,153,154,155,156,133,157,158,159,160,161,162,163,164,165],"wan 2 6 prompting","prompting","image","generate","Budget","Audio","text","animate","model","flash","only","route","time","line","input","text-to-video","image-to-video","mode","expansion",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":174,"publishedAt":44},"01M6BY47T4748ZG5ZMTAR97ZWZ","video-workflow","Build a reusable NodeTool video workflow for batches or repeated inputs. For a single finished piece, use a storyboard skill.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fvideo-workflow\u002FSKILL.md",[172,173],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},[124,41,175,109,39,176,26,177,178,30,179],"video workflow","reusable","build","batches","single",{"skillNo":181,"name":182,"nameZh":6,"description":183,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":184,"categories":185,"keywords":187,"publishedAt":44},"01M6BY4587N2SYN315SXGEMZC3","video-clone","Analyze a reference video and recreate its shot structure with a new product or cast in NodeTool.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fvideo-clone\u002FSKILL.md",[186],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[41,188,189,43,190,109,191,192,27,32,193],"video clone","clone","analyze","reference","cast","new",{"skillNo":195,"name":196,"nameZh":6,"description":197,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":198,"categories":199,"keywords":201,"publishedAt":44},"01M6BY4257C2KQYYMD9EK6DK8E","video-audio-continuity","Keep sound continuous across a multi-scene piece cut from generated video — why one clip per scene hard-cuts the audio at every boundary, when to write all the scenes into a single generation instead, the sound-design vocabulary that survives a provider's copyright filter, and how to check the length, the aspect ratio and the mix of what came back. Use when a piece has more than one scene and the video model writes its own audio (Seedance 2, Veo 3, MiniMax H3, Kling 2.6 and later), or when a cut's sound drops out at the shot changes.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fvideo-audio-continuity\u002FSKILL.md",[200],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[41,152,202,203,204,205,206,207,155,208,209,210,211,212,213,214,215,216,217,218,138],"video audio continuity","continuity","design","boundary","how","why","write","generated","later","back","across","cut","how to","filter","mix","at","veo 3",{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":223,"categories":224,"keywords":226,"publishedAt":44},"01M6BY3ZANBSQMZRH4MG55R8Z7","veo-3-prompting","Prompt Google's Veo 3 video line — the five-element shot\u002Fsetting\u002Fsubject\u002Faction\u002Fdialogue structure, the cinematography vocabulary it reads directly, duration and aspect-ratio tradeoffs, the audio and auto-fix switches per provider, and the fixes for visual drift, temporal inconsistency and audio mismatch. Use whenever the model id contains veo3 or veo-3 (fal-ai\u002Fveo3.1 and its fast, lite, image-to-video, first-last-frame and reference-to-video routes, fal-ai\u002Fveo3\u002Fimage-to-video, google\u002Fveo3.1 on atlascloud, google\u002Fveo-3 and google\u002Fveo-3.1 on replicate, kie's veo-3-1, and Gemini's own veo-3.1-generate-preview) on generate_video, animate_image, generate_video_from_references or a TextToVideo node.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fveo-3-prompting\u002FSKILL.md",[225],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[227,228,148,218,149,229,230,150,231,232,41,152,154,155,233,234,235,236,237,238,239,27,240,241,242],"veo 3 prompting","veo","google","gemini","fast","first","fal","kie","replicate","fix","auto","references","drift","preview","element","auto-fix"]