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-action-previs-video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-action-previs-video |
| description | Use when 用户要把动作构思、打斗动作、已有动作分镜/PREVIS 板、角色三视图和场景参考转成连续动作视频,重点控制动作节拍、镜头衔接、角色一致性和多板连续性。 |
用于动作预演视频:从动作构思或已有 PREVIS 分镜图出发,生成或解析动作分镜板,并结合角色三视图、场景参考和逐板视频生成,制作连续动作预演片段。
This workflow is for action choreography and previs, not general narrative production.
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。Ask which entry mode applies:
idea_to_previs_to_video: user has action idea or written choreography; generate PREVIS boards first, confirm, then video.previs_to_video: user already has PREVIS/storyboard images; analyze boards, map them into storyboard shots, then video.Do not silently downgrade previs_to_video to idea mode if the user says they already have boards but has not uploaded them yet. Ask for the boards.
Follow the JarvisHub Execution Model. Use only model and parameter choices exposed by this turn's tool list.
Map responsibilities:
If a current tool cannot parse boards, generate 15s clips, use reference_video, or assemble timelines, mark the limitation and return the best runnable plan/prompts.
Collect:
Before video generation, character three-view or sufficiently strong character reference is required for each recurring character. If missing, pause and ask.
Important: video board generation is sequential, not parallel, because later boards may depend on prior board continuity and confirmed outcomes.
Register and bind immediately after analysis:
element character,element scene,shot,[pending binding] and ask user to assign.Do not postpone asset registration until the end of storyboard work. It creates avoidable mismatch risk.
For uploaded boards, parse each panel:
If a panel is unreadable, mark it [needs user supplement]. Do not invent missing action.
Storyboard mapping per board:
board_id,frame_range,action_beat_sequence,camera_choreography,continuity_note,density: high-density action or low-density transition,target_duration.Duration:
When generating boards from an idea:
Board prompt should encode:
Keep PREVIS boards readable. Do not render realistic character detail in the PREVIS board unless the user explicitly wants final-style storyboard frames.
Each board becomes one video shot.
Each shot must include:
Continuity:
Reference priority for each board:
Use previous video reference sparingly. For many boards, reference-chain errors can compound.
For projects with 5+ boards:
If the same failure appears across 3 consecutive boards, pause and treat it as systemic: character reference too weak, scene unclear, or prompt overcomplicated.
Video prompt should not repeat everything visible in the PREVIS board. Use it to add:
Template:
Use the PREVIS board <<<image_1>>> as the primary action choreography reference. Follow the panel order and movement arrows. Preserve Character A/B/C identities from the attached character reference images. The clip begins with [starting posture/location], performs [action sequence and force quality], camera [movement], and ends with [ending state for next board]. [scene/light/style]. no subtitles, no random text, no watermark, no music.
If PREVIS board has labels/text, state that labels are production metadata and should not appear as final in-scene text.
Current board quality failure:
Continuity break:
Character drift:
Skipped board:
Check each board video:
Before final assembly, produce a board list with status and total duration.
Return:
mode,final_spec,assets: board, character, scene bindings,storyboard: board-to-shot mapping,prompts: per-board prompts,media: per-board video URLs or pending states,retry_list,assembly_plan,review.Do not present PREVIS boards as final action video.
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