Seedance Japanese Prompt Examples
Emily2040/seedance-2.0
Provides Japanese prompt patterns and safe example rewrites for Seedance 2.0 video generation, with reference tags kept intact and each example labeled by risk.
Agent skill
by CyberJ0605 in CyberJ0605/cinematic-video-prompt-engineer-skill
A skill your agent uses when the user provides a plot summary, scene idea, character relationship, emotional beat, or short video concept and wants a cinematic AI video prompt.
$ npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install CyberJ0605/cinematic-video-prompt-engineer-skill cinematic-video-prompt-engineer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cinematic-video-prompt-engineer .claude/skills/cinematic-video-prompt-engineer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "cinematic-video-prompt-engineer" agent skill from https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineer into .claude/skills/cinematic-video-prompt-engineer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cinematic-video-prompt-engineer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install CyberJ0605/cinematic-video-prompt-engineer-skill cinematic-video-prompt-engineer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/cinematic-video-prompt-engineer .agents/skills/cinematic-video-prompt-engineer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cinematic-video-prompt-engineer" agent skill from https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineer into .agents/skills/cinematic-video-prompt-engineer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cinematic-video-prompt-engineer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install CyberJ0605/cinematic-video-prompt-engineer-skill cinematic-video-prompt-engineer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/cinematic-video-prompt-engineer .cursor/skills/cinematic-video-prompt-engineer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cinematic-video-prompt-engineer" agent skill from https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineer into .cursor/skills/cinematic-video-prompt-engineer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cinematic-video-prompt-engineer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git --path cinematic-video-prompt-engineer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install CyberJ0605/cinematic-video-prompt-engineer-skill cinematic-video-prompt-engineer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/cinematic-video-prompt-engineer .gemini/skills/cinematic-video-prompt-engineer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cinematic-video-prompt-engineer" agent skill from https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineer into .gemini/skills/cinematic-video-prompt-engineer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cinematic-video-prompt-engineer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install CyberJ0605/cinematic-video-prompt-engineer-skill cinematic-video-prompt-engineerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/cinematic-video-prompt-engineer .github/skills/cinematic-video-prompt-engineer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cinematic-video-prompt-engineer" agent skill from https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineer into .github/skills/cinematic-video-prompt-engineer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cinematic-video-prompt-engineer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install CyberJ0605/cinematic-video-prompt-engineer-skill cinematic-video-prompt-engineer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/cinematic-video-prompt-engineer .opencode/skills/cinematic-video-prompt-engineer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cinematic-video-prompt-engineer" agent skill from https://github.com/CyberJ0605/cinematic-video-prompt-engineer-skill/tree/main/cinematic-video-prompt-engineer into .opencode/skills/cinematic-video-prompt-engineer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cinematic-video-prompt-engineer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
cinematic-video-prompt-engineerA skill your agent uses when the user provides a plot summary, scene idea, character relationship, emotional beat, or short video concept and wants a cinematic AI video prompt.
Cinematic Video Prompt Engineer is an agent skill from CyberJ0605/cinematic-video-prompt-engineer-skill. Use when the user provides a plot summary, scene idea, character relationship, emotional beat, or short video concept and wants a cinematic AI video prompt. First diagnose the story, then rewrite it into a model-ready prompt for Kling, Seedance, Veo, Sora, Runway, Jimeng, or general AI video models.
Its SKILL.md is about 10k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including reference files (for example `agents/openai.yaml`, `references/camera_movement_prompt_library.md` and `references/chase_action_coverage.md`).
It sits in Media & Creative, covering AI video generation and Prompt engineering. It works with Seedance. The repository describes itself as: A Codex skill for turning plot summaries into cinematic AI video prompts. It diagnoses story, emotion, structure, shot design, micro-expressions, sound, reference image prompts… The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit e24f97f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Cinematic Video Prompt Engineer loads about 10k tokens when it runs, and up to ~138k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 5,599 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from CyberJ0605/cinematic-video-prompt-engineer-skill at commit e24f97f, republished under its MIT licence (© CyberJ0605). 5,599 words, ~10,370 tokens.
.claude/skills/cinematic-video-prompt-engineer/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.This skill turns a user's plot summary, novel excerpt, or scene idea into a cinematic AI video prompt. It does not only decorate text with film words; it first identifies what can be shown in a short video, then translates abstract story into visible action, camera language, performance details, light, sound, and timing.
It can also continue a previous generated segment. When the user asks to continue, extend the story from the prior segment's ending, preserve character/scene/prop continuity, and create new reference-image prompts only for newly introduced characters, locations, products, or key props.
Apply these rules before mode/path-specific checkpoints. They work through ordinary conversation and available attachments; no named agent, special question API, persistent memory, or media-generation tool is required.
与前文无关 starts a new story state.1, 按建议, and 继续 against the most recent unambiguous pending choice; ask which choice only if more than one remains plausible.Before drafting, distinguish internally: (1) locked story facts, line wording/order, knowledge boundaries, ending and hard delivery/camera constraints; (2) technical design needed to make the supplied event visible and physically possible; (3) discretionary styling. Do not print this classification by default. Preserve category 1; choose category 2 within it; use category 3 only where helpful. Specifying an already-required button's visible position is technical design; inventing a character's decision to approach or press it is not. Do not strengthen suspicion into certainty, add an attack/intent, or silently change an outcome merely to bridge a hand/prop state. Choose a neutral compatible starting state when the input leaves it open; ask only when an unresolved foundation requires it.
For a story-critical transfer, support, threshold crossing, fall, strike, door operation or gaze/evidence change, privately trace before → visible change → after: holder/active hand and occupied contacts; footing/weight support; world-space direction, target and clearance; resulting body/prop/knowledge state. Check only dimensions involved in that event, not every body part or every gesture. Retain enough of the chain in the final prompt for the model to execute it; the internal audit is not an extra user-facing table.
For continuation, multi-shot reference-driven work, or cut/geometry repairs, read references/continuity_director_contract.md before drafting. This contract governs six controls: tail-frame versus first-frame authority and cut auditing; visible-only model instructions; shot-to-reference coverage; visible diagnosis/strategy sections; purposeful camera geometry/lens/depth; motivated camera variety. It overrides older examples that imply copying a tail frame. Run its final delivery gate before responding.
Default workshop and continuation outputs retain concise 【剧情诊断】 and 【电影化改写策略】; repeated revisions do not imply prompt-only mode. Missing new-angle evidence triggers reference prompts before final image-grounded video compilation. Explicit user scope and approval boundaries still apply.
Choose an output mode from the user's intent. Default to full workshop mode.
After choosing the output mode, choose one production path: 直接视频路径 or 参考图优先路径. Do not merge both into one universal prompt. Use the direct path for a self-contained video prompt; use the reference-first path as a staged workflow whose later video prompt assumes approved/generated reference images. Read references/reference_first_video_workflow.md only when references are requested, supplied, or materially useful.
If the user asks to continue, use the continuation workflow instead of the standard first-segment workflow.
If the user provides or describes a generated video result and asks to fix it, use Generated-Result Surgical Repair in references/style_patterns.md: diagnose the result-to-intent gap, lock successful elements, and change only the failed control unless the underlying shot structure is unsound.
For generated-video attribution, or an emotional true one-take involving near/far attention, approaching characters or shared-object contact, also read references/one_take_emotional_coverage.md. Audit readable emotional coverage, world-space facing/gaze, contact ownership and camera travel time; distinguish framing, zoom and focus transfer. Do not impose elaborate movement on simple or deliberately locked shots.
If the user provides or describes a generated reference image and asks to fix it, use Reference Image Result Repair in references/reference_first_video_workflow.md: preserve approved visual facts, change only the failed field and its physical dependents, and do not redesign the asset from scratch unless the failure is foundational.
When camera movement materially affects storytelling, the user requests a specific move, or the shot needs more precise start/path/speed/end control, read references/camera_movement_prompt_library.md. Select by dramatic function and adapt only the needed module; do not load all 46 movements into the output.
When lens/depth choices determine whether a face, shared contact, moving action or near/far group is readable, use Camera geometry before numeric decoration in references/continuity_director_contract.md: decide required evidence, subject depths and usable camera position before focal length, focus and optional aperture. Do not add numeric optical fields to every shot.
When a named emotion, emotional transition, close performance, dialogue barrier, concealment, or reaction beat needs more observable acting detail, read references/emotion_performance_prompt_library.md. Select one nearest base emotion, keep only 2-4 useful signals, and adapt them to the character rather than copying a complete stock expression.
Resolve aspect ratio without adding routine friction. Follow an explicit ratio, inherit the actual first-frame/approved continuation ratio, and preserve a confirmed series ratio. If nothing indicates otherwise, default ordinary low-risk work to 16:9横屏 without asking. Ask once only when the ratio cannot be inferred and would materially change production references, two-person/group blocking, full-body action, fight/dance/chase, architecture/landscape/vehicle scale, or a multi-platform master; merge the question with any existing direction or production-path checkpoint. When vertical/portrait/9:16 is selected, read references/vertical_9x16_adaptation.md and recompose for the narrow frame rather than cropping horizontal grammar.
Output modes:
精简模式: final video prompt only; use only when the user explicitly says 直接给提示词, 不要分析, 只要成品, 只输出最终提示词, or 精简模式.打磨模式: diagnosis, strategy, and the deliverable for the current production path/stage; default for ordinary creation and revision. Do not force reference prompts and a final video prompt into the same response.方向确认模式: diagnosis, strategy, and the specific unresolved decision only; use when the execution rules above require clarification or the user explicitly reserved approval.连续短片模式: continuity summary, character bible, scene continuity sheet, references, segmented/continued prompts, and clip-bridging instructions; use for multi-part stories or repeated continuation.Use 方向确认模式 only when:
🔴 CHECKPOINT · Direction selection: In 方向确认模式, stop after the following sections and wait for the user's choice or explicit delegation:
【剧情诊断】
...
【电影化改写策略】
...
【需要你确认的方向】
1. ...
2. ...
3. ...While this direction decision is unresolved, do not output reference prompts or the final video prompt. Once the user selects or delegates that decision, continue with the deliverable for the chosen production path and actual asset state. Do not ask the same question again or treat direction approval as image approval.
参考图优先路径 without another route question.直接视频路径 without another route question.直接视频路径; do not add a route checkpoint merely because a reference image could help.这类场景建议先建立参考图。你要走参考图优先,还是直接生成完整视频提示词?参考图优先路径 for the high-drift cases above and 直接视频路径 for simple low-drift scenes.In 参考图优先路径, wait only when required actual images are unavailable/unreadable or the user reserved an image-approval step. If images are already supplied, selected, and readable, inspect them and proceed without repeating Stage 1. If actual generation and continuation are authorized, use available tools, inspect results, and continue unless user approval was reserved. If the user requests a complete text package before images exist, label the later video draft as provisional and not compiled from actual images; never invent image verification.
剧情诊断
Short-Drama Hook and Narrative Drive Diagnostic in references/style_patterns.md. Check anomaly, immediate goal, rule/cost, active obstacle, information reversal, and unresolved question as optional functions, not mandatory ingredients. Do not apply this formula by default to emotional close-ups, atmosphere pieces, product films, action demonstrations, or already complete plots.Character Knowledge and Evidence Control system in references/style_patterns.md: preserve what the character already knows, what new evidence they observe, what they may reasonably infer, and what must remain unknown. Do not let a character react to information the screenplay has not yet made available to them.Retrospective Reversal and Dual-Meaning Montage System in references/style_patterns.md. Track objective truth, character perception, and audience belief separately; pair earlier and later beats through action, composition, motion direction, contact, or sound; and reveal enough final evidence to change the earlier meaning without explanatory narration. Do not force this system onto ordinary emotional scenes or add an unsupported twist merely to use it.references/style_patterns.md: single take, multi-shot sequence, jump cuts, montage, continuous action editing, dialogue cross-cutting, close-up micro-expression, product/person texture film, large-scene compression, or another fitting form.电影化改写策略
活人感处理 note: name the character's psychological motive and how eye line, expression, pause, voice, incidental body language, contact, environment response, and camera conditions should stay consistent.台词表演控制 note: state the character's purpose, emotion barrier, trigger words, pauses, breath, facial/body changes, and what reaction must not happen too early.建议先生成的参考图
直接视频路径, omit this section by default. A brief optional recommendation is enough when references would improve control; do not also dump full image prompts unless the user asks.参考图优先路径, provide only missing asset planning/image prompts for the requested stage. Apply the availability and approval conditions in Production Path Routing; skip asset creation for usable, selected images already supplied.最终视频提示词
直接视频路径, make it self-contained: include the minimum character, setting, costume, prop, light, and start-state anchors needed to work without images.参考图优先路径, compile it from the actual approved/generated images. The pixels in the selected images outrank their earlier image prompts: do not treat a planned prop, costume detail, pose, or layout as present unless it is visibly confirmed. Do not repeat full static descriptions. State a compact reference-authority mapping, then prioritize story structure, duration, action order, performance change, shot-size/angle development, camera movement, dialogue/lip-sync, sound, transitions, and ending state. Describe any intended change from a reference as an explicit timed delta with cause and final state.参考图驱动版 and 无参考图直出版. Do not make one ambiguous prompt serve both purposes.剧情诊断, 电影化改写策略, or optional reference-image prompts. Do not treat the ceiling as a target length.Prompt Compression in references/style_patterns.md under the dialogue and coverage controls in Execution Gates and Failure Recovery. Older instructions to shorten dialogue are not permission to edit supplied key lines: simplify decorative detail, redundant constraints and secondary camera/action first; edit such lines only within the user's authorization. A scope conflict still requires the specific choice, not silent omission.ECU, CU, MS, MLS, Dolly In/Out, Pan Right/Left, Tilt Up/Down, Track Right/Left, Rack Focus, 35mm, or Handheld. Write action, emotion, performance, lighting effect, sound, causality, and story instructions in Chinese; do not paste English library sentences into the final prompt.整体声音与光影 block when it improves continuity. Follow the placement hierarchy in references/style_patterns.md.references/style_patterns.md. Do not print the checklist unless the user asks for critique or debugging.When the user does not specify a model, assume a high-capability Seedance 2.5 / Kling 3.0 class video model that can support longer coherent prompts, but still choose duration from the story rather than defaulting to 30s. Do not add a separate generic model field. This skill does not maintain separate model-adaptation branches for now.
Resolve the following conditions before writing the final prompt:
| Trigger | First response | If it still cannot fit or stabilize |
|---|---|---|
| A story foundation is unresolved and cannot be inferred or chosen within delegated creative control | Ask one concise question covering only that missing foundation | Once resolved or delegated, choose one coherent interpretation and proceed; do not restart other confirmed choices |
| The requested events cannot play within one 30-second clip | Preserve the requested coverage: select a highlight only for highlight scope; use numbered clips for full coverage | If full coverage and a hard single-clip limit conflict, explain the concrete conflict and ask which constraint may change; do not silently omit events |
| Dialogue timing is dense or uncertain | Run a dialogue playability audit: judge local speaking pace, interruption, overlap, pauses, failed starts, listener reactions, and ending residue; word count and average speech rate are risk signals, not automatic deletion rules | If the intended performance still cannot complete naturally, preserve key lines and first simplify shots, camera, blocking, and decorative detail; then explain the conflict and offer a split or user-approved line edit instead of silently deleting dialogue or forcing an unnatural delivery |
| The final prompt exceeds the duration-based ceiling | Apply the compression ladder in references/style_patterns.md | Simplify decorative shots/actions; split only within authorized coverage and clip constraints, otherwise ask about that conflict. Preserve causality, key dialogue, continuity anchors, and the final reaction |
| Spatial, prop, costume, or emotional continuity is uncertain | Reconstruct the last confirmed state and list the minimum continuity anchors | Use a neutral re-establishing shot or a new clip boundary; do not invent an invisible reset |
| The user requests conflicting camera instructions | Preserve the requested dramatic function and choose one physically plausible camera path | State the single conflict that was resolved; do not stack incompatible moves |
| A requested reference image would introduce unwanted people or visual drift | Separate identity, relationship, scene, and prop references by production purpose | Omit the unnecessary reference and restate the stable visual anchors inside the video prompt |
| Actual reference images differ from their original prompts or contain unclear story-critical details | Treat the visible image as the source of truth; inventory confirmed, absent/unclear, conflicting, and contaminated fields | Repair/regenerate the asset, add a compatible dedicated reference, or redesign the action around what is visibly present; do not silently inherit the plan |
| A supplied reference contains a watermark, logo, garbled text, malformed anatomy, crop, or obstruction likely to propagate | Flag the issue before compiling the production prompt and recommend a clean, repaired, or cropped asset | Do not rely on a negative prompt to erase content already embedded in the reference |
| A reference-driven action may conflict with the visible hand position, furniture, reach, clearance, weight, friction, or exit path | Run the physical-feasibility audit in references/reference_first_video_workflow.md and rewrite the contact/action chain | If the motion cannot be made credible from the selected image, repair the keyframe, change the blocking, or split the action |
| Aspect ratio is unspecified and would materially change expensive reference generation or complex blocking | Combine one 16:9横屏还是9:16竖屏 question with any existing checkpoint | If the user delegates, default to 16:9 unless an actual vertical production asset or explicit vertical delivery context controls the choice |
| Vertical/9:16 output is explicit, inherited, or confirmed | Read references/vertical_9x16_adaptation.md; redesign composition, coverage, movement, and reference frames for a narrow canvas | Simplify/group shots, add a vertical keyframe, or make a separate vertical adaptation if essential width cannot survive |
🔴 CHECKPOINT · Adaptation scope conflict: 完整改编 / 完整覆盖 / 连续短片 already select full coverage; 选最强片段 selects highlights. Do not re-ask that choice. Build the appropriate structure before detailed prompts, then continue the requested deliverable unless the user requested structure-only/approval-first or required assets are missing. Pause only for an unresolved material scope conflict, such as full coverage plus an unworkable hard single-clip limit. Input length alone is not a checkpoint.
references/style_patterns.md, subordinate to requested coverage. A short passage may need multiple clips; a long passage does not by itself require an approval round. Establish the selected scene or continuous structure first, then deliver the requested prompts while preserving cause and effect.Apply Execution Decisions and Agent Capabilities. Ask one concise question only when a necessary story foundation remains unresolved after checking the brief and delegated creative control, for example:
Do not ask for missing technical details such as lens, lighting, camera movement, sound, micro-expression, or pacing. Fill those in cinematically. If the user says to freely create, do not ask.
For continuation or continuous multi-clip stories, read references/continuation_workflow.md and the continuity contract before drafting. Preserve story/prop/emotional state, not an obligatory duplicate tail-frame composition. Do not load this module for unrelated first-segment work.
Default format is workshop mode. Keep diagnosis and strategy visible so the user can correct the interpretation before reusing the production deliverable. Keep these sections concise. The chosen production path determines what follows: a direct-video prompt, or the current reference-first stage. Do not show empty sections.
For detailed mode selection and templates, use Output Modes in references/style_patterns.md.
Direct-video workshop format:
【剧情诊断】
情绪核心:
视觉核心:
结构判断:
时长判断:
取舍与补全:
【电影化改写策略】
...
【最终视频提示词】
基础概括:
...Reference-first Stage 1 format:
【剧情诊断】
...
【电影化改写策略】
...
【参考图素材规划】
本阶段需要:
不单独生成:
【参考图提示词】
参考图1|类型与用途:
提示词:After the actual images are generated, selected, or supplied, use the reference-driven prompt shape in references/reference_first_video_workflow.md.
For the final prompt, include the sections that matter for the scene. Do not force every label if it makes the prompt bloated. Use negative constraints selectively: choose only the scene-specific risks that are likely to harm generation, instead of repeating a long generic list.
Use a compact summary and timed shot/action beats. Choose only the scene-relevant components: composition, camera, performance, dialogue, light, sound, ending and likely failure constraints. These are a field menu, not mandatory headings; lens/aperture numbers, voice profiles and micro-expression ladders are conditional controls, not a completeness checklist.
State stable identity, spatial layout, light, sound bed and global constraints once at scene level; shot beats describe the changes and any local state needed to understand them. Repeat a critical contact, occupied hand, support, gaze target or prop ownership when a cut or transfer would otherwise make it ambiguous. Do not remove these facts to meet a shorter target. Avoid restating the same unchanged constraint in the summary, every shot and the ending; a longer duration alone does not require more fields or padding.
Do not include a separate 视频模型 line by default. If the user specifies a model, adapt the prompt to it naturally. Put duration and structure into 基础概括, for example: 基础概括:这是一段18秒连续情绪对话....
Read only applicable sections of references/director_modules.md before drafting:
| Task evidence | Section |
|---|---|
| Any final video prompt; structure, compression, novel or plot turn | Structure and delivery; Visible motion |
| Multi-shot, camera movement, first-frame control, contact/route visibility or one-take | Camera and spatial evidence; use continuity_director_contract.md when its scoped controls apply |
| Human emotional/dialogue/reaction performance | Performance and dialogue |
| Fight/action choreography | Fight choreography, plus applicable camera/performance sections |
| Pursuit, escape, interception or obstacle-driven distance changes | Chase and escape; read references/chase_action_coverage.md for causal motion and genre-matched coverage |
| Dramatic color/light design or night/period visibility | Light and color; otherwise the compact main-file light baseline is sufficient |
| Dialogue, offscreen evidence, sound perspective or changing acoustic space | Sound; simple scenes retain the main-file sound bed without elaborate audio fields |
| Animals, robots, unequal height or body geometry | Non-human and unequal geometry |
| Multiple people or inhabited public locations | Ensemble and background |
These modules retain the existing director controls. They are not a reason to add ingredients, load every library, or expand the output. Locate referenced style_patterns.md headings and read the complete selected section, not the whole library. If no precise module applies, use the core workflow; do not invent a requirement from a genre label.
When planning or writing reference-image prompts, read references/reference_prompt_content.md for identity, scene, relationship and prop controls. Read references/reference_first_video_workflow.md for stages and actual-image authority. Skip both for an explicit no-reference direct prompt unless a relevant image-repair dependency exists.
Do not:
电影感, 高级感, 史诗感, or 氛围拉满 in place of concrete action, light source, sound, composition, and timingWhen more guidance is needed, read references/style_patterns.md. It contains the evolving house style extracted from user-provided cinematic prompt examples. Update that reference when the user shares better prompt examples and asks to improve the skill.
When testing, reviewing, or revising this skill, read references/evaluation_cases.md. Use its applicability-aware rubric, fixed core regression selection and separate text/image/video evidence records; run the cases affected by the change and representative unchanged controls. Do not load the evaluation set or print scorecards during ordinary prompt generation.
During maintenance, explicit user requirements control the task; preserve current confirmed story/asset state and applicable continuity constraints before optional treatments or examples. Scope the continuity contract's precedence to the controls it governs. Case expectations and example templates test those rules; they do not override user choices or turn sample shot counts, lens values, emotion ladders or reference budgets into universal requirements. If current governing rules conflict, reconcile their source and tests rather than leaving the conflict to the receiving model.
Keep the current creative rules stable after an accepted revision. New successful samples may enter the example/test set without changing global rules. Change a rule only for a demonstrated generalizable gap or repeatable failure; preserve successful controls, make the narrow repair, and record its affected-case retest. Do not call the skill mature from one high score or a single successful render.
© CyberJ0605, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 15 other files (references) in cinematic-video-prompt-engineer of CyberJ0605/cinematic-video-prompt-engineer-skill.
Open the folder on GitHubat commit e24f97f
Cinematic Video Prompt Engineer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cinematic Video Prompt Engineer this skillCyberJ0605/cinematic-video-prompt-engineer-skill | 127 | — | ~10k | Automated safety check: Pass | MIT | |
| Seedance Japanese Prompt ExamplesEmily2040/seedance-2.0 | 7.6k | 1 repos | ~898 | Automated safety check: Pass | MIT | |
| Realistic AI Video Prompt Writerzhouwei713/seedance-prompt | 327 | — | ~749 | Automated safety check: Pass | MIT | |
| Seedance 2.5 Video PlannerAtlasCloudAI/awesome-seedance-2.5-prompts-skills | 234 | — | ~4.3k | Automated safety check: Pass | Custom licence | |
| Seedance Prompt LibraryLearnPrompt/awesome-seedance | 1.9k | — | ~1k | Automated safety check: Pass | MIT | |
| Video Prompting GuideNeverSight/learn-skills.dev | 217 | 1 repos | ~2k | Automated safety check: Pass | None |
Emily2040/seedance-2.0
Provides Japanese prompt patterns and safe example rewrites for Seedance 2.0 video generation, with reference tags kept intact and each example labeled by risk.
zhouwei713/seedance-prompt
Turns a vague video idea into a seven-section prompt that reads like real home-video, phone, DV or surveillance footage, with checks against an AI-look checklist.
AtlasCloudAI/awesome-seedance-2.5-prompts-skills
Plans and generates controllable Seedance videos by choosing a creative route first, from text prompts and storyboards to keyframe pairs, extensions and edits.
LearnPrompt/awesome-seedance
Verified prompt templates and structures for Seedance 2.5 / 2.0 video generation, distilled from the highest-performing published cases on goodcase.ai.
NeverSight/learn-skills.dev
Best practices and techniques for writing effective AI video generation prompts.
Emily2040/seedance-2.0
Routes Seedance 2.0 video work across Dreamina, API and router surfaces, covering prompts, reference handling, audio and lip-sync, pricing and model-ID questions.
Works with
Categories
A skill your agent uses when the user provides a plot summary, scene idea, character relationship, emotional beat, or short video concept and wants a cinematic AI video prompt. Cinematic Video Prompt Engineer is an agent skill from CyberJ0605/cinematic-video-prompt-engineer-skill. Use when the user provides a plot summary, scene idea, character relationship, emotional beat, or short video concept and wants a cinematic AI video prompt.
Cinematic Video Prompt Engineer fits situations like: the user provides a plot summary; character relationship; short video concept and wants a cinematic AI video prompt.
Run `npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a claude-code`. Or copy the skill folder (cinematic-video-prompt-engineer in CyberJ0605/cinematic-video-prompt-engineer-skill) into .claude/skills/cinematic-video-prompt-engineer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a codex`. Or copy the skill folder (cinematic-video-prompt-engineer in CyberJ0605/cinematic-video-prompt-engineer-skill) into .agents/skills/cinematic-video-prompt-engineer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CyberJ0605/cinematic-video-prompt-engineer-skill --skill cinematic-video-prompt-engineer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cinematic-video-prompt-engineer, .gemini/skills/cinematic-video-prompt-engineer, .github/skills/cinematic-video-prompt-engineer and .opencode/skills/cinematic-video-prompt-engineer in your project.
SKILL.md names no scripts, command-line tools or credentials: Cinematic Video Prompt Engineer is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Cinematic Video Prompt Engineer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 10k tokens (SKILL.md is roughly 41k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 128k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Cinematic Video Prompt Engineer: Seedance Japanese Prompt Examples (Emily2040/seedance-2.0, 7.6k stars), Realistic AI Video Prompt Writer (zhouwei713/seedance-prompt, 327 stars), Seedance 2.5 Video Planner (AtlasCloudAI/awesome-seedance-2.5-prompts-skills, 234 stars) and Seedance Prompt Library (LearnPrompt/awesome-seedance, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
CyberJ0605 (a GitHub user) maintains it in CyberJ0605/cinematic-video-prompt-engineer-skill, which has 127 GitHub stars. The repository was last updated on October 10, 2026.
Source: CyberJ0605/cinematic-video-prompt-engineer-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.