用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/LYL1015/JarvisHub --skill flova-one-shot-continuity-film命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | flova-one-shot-continuity-film |
| description | Use when 用户要生成一镜到底广告短片、影视长镜头、高连贯性故事短片、连续运镜、前一镜头末帧承接下一镜头、顺序生视频或需要逐镜确认的短片。 |
用于一镜到底连续短片:用首帧承接、前置视频参考或物理连续调度,让多个镜头看起来像一个连续长镜头短片。
This is a strict sequential workflow. Do not parallelize shot generation for this skill, because Shot N depends on Shot N-1's final frame or reference video.
imageUrl / videoUrl,不能把提交态当完成态。critic sub-agent:只读取真实媒体并评审,不生成、不补素材。blocked 项,除非本轮工具列表明确暴露对应能力。This workflow uses the JarvisHub canvas execution model. Use the JarvisHub canvas harness tools and subagents for asset binding, image/video generation, frame extraction, and final assembly.
If the this turn's tool list cannot extract the last frame, cannot use reference_video, or cannot use start/end frames, state the limitation and choose the closest supported execution path. Do not claim seamless continuity when the required reference chain was not actually used.
Use this skill for:
Do not use this skill for high-energy beat-cut montages. Use flova-beat-cut-motion-video for that. For long narrative films with many scenes, use canvas-long-video-production first and apply this skill to a specific continuous sequence.
Collect or infer:
brief: brand/product/story goal.duration: total duration and approximate shot count.aspect_ratio: platform target; default to 9:16 for short-video ads, 16:9 for cinematic ads.continuity_mode: last_frame_bridge or reference_video_bridge.visual_style: cinematic style, color grade, lighting, tone.language: exact dialogue/VO language if there is speech.provided_assets: uploaded product/character/location/music/voice references.confirmation_policy: whether the user wants to confirm every shot; default yes for production runs.If the user has not selected a continuity mode, explain the tradeoff briefly:
last_frame_bridge: faster and cheaper; can have slight "brake" or still-frame feeling at seams.reference_video_bridge: smoother motion continuity; slower and more expensive if supported.When the user asks for immediate execution and has not chosen, default to last_frame_bridge unless they explicitly prioritize maximum smoothness.
Never batch-generate Shot 2+ before Shot 1 is accepted.
Design fewer, longer shots. A "one-shot" effect benefits from internal movement rather than many disconnected cuts.
For each shot include:
shot_idduration_targetscene_element_idcharacters_or_productsopening_stateending_statecamera_movementsubject_actionspace_changedialogue_or_vocontinuity_bridge_from_previousFrom Shot 2 onward, the opening state must explicitly match the previous shot's ending state:
Avoid teleporting the subject or changing location abruptly unless the transition is an intentional match cut and the prompt states how the visual match is achieved.
Before generating:
Character reference images should show the key identity clearly. If one character needs multiple looks, name each look, such as Look_1_workwear, Look_2_evening.
Do not generate duplicate assets when a user-provided asset already satisfies the slot.
Use when the harness can extract a still image from the previous video and pass it as the next shot's start frame or reference image.
Shot 1:
Shot N where N > 1:
Use when the harness can pass the previous shot video as a reference video.
Shot 1:
Shot N where N > 1:
This mode should be selected only when the this turn's tool list supports reference-video conditioning and the user accepts higher cost/latency.
When the user dislikes Shot N after later shots already exist:
If end-frame generation is not supported, regenerate Shot N and then consider regenerating Shot N+1, because continuity may no longer match.
For every video prompt, describe motion in this order:
For last_frame_bridge Shot N > 1, include:
The video starts from <<<image_1>>>, which is the final frame of the previous shot. Preserve the subject position, camera scale, lighting direction, and motion direction from <<<image_1>>> before continuing the camera move.
For reference_video_bridge Shot N > 1, include:
Continue from the ending of <<<video_1>>>. Preserve the last visible subject pose, camera direction, lighting, and spatial momentum, then continue the one-shot camera movement naturally.
For a regenerated middle shot with start/end references, include:
Start from <<<image_1>>> and transition smoothly so the final frame matches <<<image_2>>>. Maintain character/product identity, lighting continuity, camera direction, and spatial layout between both references.
Always include negative constraints:
If the storyboard has separate narration, do not put the narration script inside the video prompt unless the current video model is meant to generate speech.
The visual seam should be a pure cut when start/end continuity was generated correctly. Do not add dissolves, white flashes, or decorative transitions to hide errors unless the user asks for stylized transitions.
Audio should remain continuous across shot seams:
If the harness supports timeline assembly, assemble only accepted shots. If not, return the accepted shot URLs and an explicit assembly plan.
For each generated shot, verify:
Before moving from Shot N to Shot N+1, ask for confirmation when doing an interactive production run. For fully autonomous runs, use the critic result as the confirmation substitute and log the decision.
Return:
spec: title, duration, aspect ratio, style, language.continuity_mode: chosen bridge mode and why.storyboard: ordered shot table with opening/ending continuity notes.assets: reused and generated assets.shot_generation_log: per-shot input references, video URL, review result.assembly: final video URL or assembly plan.issues: any failed bridge, missing harness capability, or shot needing regeneration.Do not describe the film as "one-shot" if shots were generated independently without frame/video bridging.
Use when the user asks JarvisHub AI Chat or a `webHero` workflow to generate a website, landing page, homepage, brand-style web design, preview-first webpage workflow, or wants section screenshots, webpage assets, and final HTML to be produced as one staged flow.
把 assets/demo 提炼成运行时可用的视觉连续性方法论:先锁资产/角色/场景/镜头语义,再做扩镜与视频。(素材生成场景:角色一致性、视觉锚点锁定、单素材生成前的锚点规范与一次只改一个变量。)
基于用户提供的设计稿图片还原真实网页。该 skill 可用于任意前端项目,但强依赖本地已启动且已授权的 JarvisHub vision 工作流;视觉模型由服务端默认配置决定,支持外部传入 vision prompt,且不可静默降级。
基于 SOC 职业分类