Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.
npx skills add https://github.com/Alisa0808/vibe-creating-skill --skill vibe-creating-prompt
Vibe Creating distills what the user *actually wants to express* so the model can lock onto the visual center, the emotional direction, and the continuity of the experience. It amplifies creative intent, emotional value, key imagery, and visual coherence; it down-weights low-value technical parameters and mechanical execution language.
This skill is a *judgment-first* rewriter. It does not blindly shorten or "vibe-ify" everything. It first asks whether the input even belongs in the Vibe Creating lane, then chooses the lightest action that serves the user's intent.
When you receive an input, run three steps:
Do not expose internal labels (S1, E2, "Mode 5", etc.) to the user. Judge internally; communicate plainly.
Decide along three axes. First Scenario (S) — does the underlying creative goal suit VC. Then Expression (E) — what form is the user's text already in, which sets *how much* to touch. Information density (I) runs in parallel as a stability check: whenever a must-have is missing, ask first, then route.
| | E1 — close to VC | E2 — mixed | E3 — precision control |
|---|---|---|---|
| S1 — VC-native | Direct rewrite; if already polished → light cleanup or pass-through | Light cleanup, then rewrite — keep valid structure, order, emotional build | Treat as *VC-translatable*; strip low-value technical control, convert to natural visual description. Don't reject just because it's written as an execution script |
| S2 — partial | Light cleanup; if already usable → pass-through | Offer an *optional* VC version; let the user choose | Keep the original intent; gently note a VC rewrite is available on request |
| S3 — low fit | Stay close to the original; keep as-is if needed | Keep as-is or do very limited cleanup; only stylize on explicit request | Keep as-is; explain this fits a traditional shot-list workflow better than VC |
Even a VC-perfect scenario can't be force-rewritten when a key element is missing. Ask first when: there's no clear visual anchor; only an abstract feeling with no subject/object/scene; a subject but no action or state; fragments with no main relationship or style direction; an ultra-short input that has a subject and event but no clear style/viewing-mode/key moment; or multi-shot content with jumps you can't see a reason for.
A strong VC prompt prioritizes these four layers. Fill whichever is missing first — don't mechanically demand all four:
Asking principle: the density check is not a separate gate — it runs alongside S and E. Ask for the minimum needed to land the chosen action, usually in one round. For ultra-short, abstract, single-image inputs, prioritize turning the abstract word into the visible information a frame needs; if the direction is already mostly clear, give a first pass and ask about only the most critical 1–3 gaps.
Internally complete the three judgments (S / E / I) — preliminary judgments are fine when info is short. Then choose an action:
> pass-through · light cleanup · direct rewrite · ask first · keep as-is · optional VC version
Handling principles:
Camera language should not be deleted wholesale. What to remove is the low-value "tell the system how to shoot" technical parameters. What to preserve or translate is the "how should the viewer feel" intent.
Demote or delete by default:
Translate intent instead of dropping it — e.g. "slow dolly-in" → "the gaze slowly closes in, building a sense of pressure."
When the user explicitly asks to keep parameters: obey the constraint first, then decide whether to *additionally* offer a VC version.
When it's undeclared whether to keep precision control:
Dialogue, voiceover, music, SFX, lyrics, narration, and other explicitly specified sound content rank above creative optimization. You may reorder them, but you must not reword them, replace them, or delete a user's explicit sound requirement.
When rules conflict, resolve in this order:
Supplementary rules:
VC rewriting is not one template. Pick the mode by the input's dominant factor:
The goal is to help the user express more accurately — not to rewrite their work into a different film.
S1 + E2 or Mode 5.| Input type | Judge first | Ask what's missing | Default action | Output style |
|---|---|---|---|---|
| Single scene with clear subject, action, mood | Likely suits VC; check if already focused enough | Only if style, visual center, or main state is missing | Direct rewrite, light cleanup, or pass-through | One ready-to-generate prompt |
| Multi-shot narrative serving one unified experience | Suits VC; check the emotion / theme / memory line is coherent | If shot-to-shot relationship or progression is unclear | Rewrite keeping structure; group if needed | Segmented, or keep original structure |
| Heavy shot numbers/params, but underlying emotion/story scene | VC-translatable; don't reject for execution style | If the main experience/action/relationship is unclear | De-noise and translate, keep narrative & emotional intent | Strip params, convert to natural visual description |
| Brand showcase, character showcase, stylized ad | Partial VC fit; rewrite not mandatory | If the emotional goal or style direction is unclear | Light cleanup or optional VC version | Keep intent; offer a more experiential version if useful |
| Only abstract words ("freedom", "premium", "powerful") | Insufficient info; don't force a rewrite | Visual anchor, scene, action, or state | Ask first; don't rewrite blind | Pose 1–3 short questions |
| Visuals already include dialogue / VO / music / SFX | Partially VC; sound content has priority | Only if the visual part is under-specified | Keep sound content; rewrite visuals only | Note "sound kept unchanged" up front |
| User explicitly wants shot numbers / params / delivery structure kept | Constraints win; don't delete | Usually no need to ask | Keep as-is, or add an optional VC version | Note "kept as the execution draft" |
| Functional demo, UI tutorial, step instructions | Low fit; the goal isn't creative translation | Usually no VC questions | Keep as-is; suggest splitting if useful | Explain VC isn't recommended |
| Long-form story requiring exact dialogue sync | Low fit; capability/workflow boundary | Usually no VC questions | No VC rewrite; suggest splitting visual segments | Explain pure-visual parts can be split out |
| Mixed-language creative input with some jargon | If the underlying experience is clear, still suits VC | Only if subject, relationship, or style is unclear | Translate jargon, keep core vibe | Output a natural visual description in the target language |
> Generating the result: this skill only writes the prompt. To render it, send the rewritten prompt to any text-to-video model (Seedance, Sora, Kling, Veo, …) — for a one-API option, see Atlas Cloud.
agent-im 会话技能 - 通过 liblib.tv 的 AI 能力生成和编辑图片/视频。覆盖场景包括:生成(文生图、文生视频、图生视频、做动画、画一个xxx、来段xxx)、编辑修改(把xxx换成yyy、去掉xxx、加上xxx、改成xxx、调整xxx、局部修改、改镜头)、风格转换(风格迁移、转绘、换风格)、视频续写延长、复刻视频/TVC/宣传片、短剧/短漫剧生成、音乐MV生成、产品广告/展示片制作、分镜/故事板设计、教育视频/短视频制作。当用户提到 liblib、libtv、上传参考图/视频、查看生成进度时也应触发。关键判断:只要用户的请求涉及 AI 图片或视频的创作、生成、编辑、修改,无论措辞如何(如"画只猫"、"做个海报"、"把纸船换成爱心"、"这个视频帮我改一下"、"帮我复刻这段视频"、"用这首歌做个MV"、"一句话生成短剧"),都必须触发此技能。
This skill should be used when the user asks to "generate video prompts", "create Seedance prompts", "write video descriptions", mentions "Seedance", "seedance", "即梦", "即梦平台", "视频提示词", "视频生成", "AI视频", "短剧", "广告视频", "视频延长", or discusses video prompt engineering, AI video generation, or Seedance 2.0 workflows.
Best practices and techniques for writing effective AI video generation prompts. Covers: Veo, Seedance, Wan, Grok, Kling, Runway, Pika, Sora prompting strategies. Learn: shot types, camera movements, lighting, pacing, style keywords, negative prompts. Use for: improving video quality, getting consistent results, professional video prompts. Triggers: video prompt, how to prompt video, veo prompts, video generation tips, better ai video, video prompt engineering, video prompt guide, video prompt template, ai video tips, video prompt best practices, video prompt examples, cinematography prompts
This skill is a practical, 'use-it-while-debugging' reference for getting a LiveKit + Letta voice agent working reliably.
Download screenshot baselines from the latest CI run and commit them. Use when asked to update, accept, or refresh component screenshot baselines from CI, or after the screenshot-test GitHub Action reports differences. This skill should be run as a subagent.
| Turn vague taste, screenshots, URLs, product notes, or "make it feel like this" references into a grounded DESIGN.md plus an implementation handoff. Use it before prototypes, decks, redesigns, or image remix work when the user needs a reusable visual direction rather than a one-off prompt.
>- Upload local assets (images, mockups, extracted HTML, design markdown) to a Stitch project. ALWAYS use this skill when you need to upload visual assets, HTML pages, or design docs to Stitch, particularly when direct MCP tool calls fail or truncate due to base64 token limits.
This skill helps users automatically extract channel-level and video detail data from a specific YouTube channel via BrowserAct API. Agent should proactively apply this skill when users express needs like extracting channel video data, getting latest or popular videos from a YouTube channel, tracking competitor channel content, extracting video metrics such as views likes comments, retrieving subscriber count and channel info, monitoring posting cadence of a YouTube channel, gathering video data for content strategy analysis, getting earliest videos of a YouTube creator, analyzing engagement signals across a full channel, and downloading structured YouTube video details without manual scraping.
Take alisa0808/vibe-creating-prompt from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.