Plan draft video-ad variations from supplied performance evidence, preserving the distinction between observed data and creative hypotheses.
中文简介正在准备中。当前显示原文说明。
Analyze a script or existing edit, identify visual gaps, and generate supplemental B-roll coverage with clear parent and factual-status labels.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Supply visual coverage that supports an approved narration, interview, or edit without overwriting the story or pretending that generated imagery is factual footage. Work from a script, transcript, edit decision list, or explicit gap list. Return clips that an editor can place by scene and time range.
If the source is a current event, historical claim, medical topic, public figure, or real-world demonstration, require verified source footage or label every generated shot as illustrative. Do not generate a plausible scene and call it evidence.
For each gap, record:
coverage_id / source timecode:
narration or edit purpose:
visual subject and action:
literal versus illustrative status:
reference roles and preservation rules:
shot size / camera / light:
duration / ratio / audio:
acceptance check:
Prefer varied coverage—establishing, detail, hands/product interaction, environment, abstract texture, and transition—without changing the intended meaning. Keep one visual idea per clip and avoid random montage filler.
literal-source, illustrative-generated, or abstract-generated.Do not generate a replacement for missing source evidence, hide a failed gap, or silently insert generated footage into an approved edit.
Return a gap/coverage table, parent/source IDs, model/endpoint, prediction IDs,
output URLs, literal/illustrative labels, placement notes, QA findings, and
failed candidates. Save permitted manifests and receipts under .video/ using
reports-and-receipts.md.
This skill creates draft coverage, not a claim of what happened in the world.
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Plan draft video-ad variations from supplied performance evidence, preserving the distinction between observed data and creative hypotheses.
中文简介正在准备中。当前显示原文说明。
Create authorized presenter, avatar, and UGC-style video drafts with explicit voice, likeness, consent, and synthetic-media handling.
中文简介正在准备中。当前显示原文说明。
Build a consented continuity system for an authorized person, fictional character, product, or world across video shots.
中文简介正在准备中。当前显示原文说明。
Translate creative intent into coherent cinematography, framing, camera, lens, lighting, motion, and sound direction for a video shot.
中文简介正在准备中。当前显示原文说明。
Create a non-explicit romantic scene from authorized adult references with clear consent, identity boundaries, and synthetic-media labeling.
中文简介正在准备中。当前显示原文说明。
Turn one approved topic into a curiosity-led 3D educational short with character sheets, ordered keyframes, motion clips, narration, captions, and an auditable assembly plan.
中文简介正在准备中。当前显示原文说明。