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SeeVido Video Prompt Architect

该工具核心是将模糊视频创意转化为生产级视频指令，可生成结构化提示包、参考序列、连续性规则及定向调试方案。支持文本转视频、图转视频等多工作流，适用于产品剪辑、电影场景、社交视频等制作场景。输入为用户提供的视频创意细节，输出为单镜头提示或多镜头分镜计划，附连续性约束、避坑清单，可选MCP工具辅助高效生成。

gpt-img-2
gpt-img-2
热度 7.62
最近更新 2026-08-27 09:24:49
分类：创作依赖：MCP 服务 / 纯提示词应用场景：视频编辑 / 文案创作 / 故事创作

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add seevido-video-prompt-architect
Metadata
name
seevido-video-prompt-architect
description
Turn rough video ideas into structured English or Chinese prompt packs, reference-aware sequences, continuity rules, and focused debugging loops. Use for text-to-video, image-to-video, reference-to-video, video-to-video, product clips, cinematic scenes, or multi-shot work; do not use for account support, live model comparisons, or claims about official provider behavior.
metadata
{"openclaw":{"homepage":"https://seevido.org/ai-video-generator","version":"1.0.0"}}

SeeVido Video Prompt Architect

Turn one clear visual idea into production-ready video instructions. This Skill is a text-only workflow by default. Its optional MCP adds deterministic, read-only helpers and never generates media, calls a provider, reads an account, compares live prices, or spends credits.

SeeVido is an independent AI media workspace. Do not present this Skill, the MCP, or the site as official documentation for Seedance, Kling, Wan, Grok, Veo, or any other provider or model.

Gather the minimum brief

Ask only for details that materially change the result. Infer ordinary creative choices when enough context already exists.

Identify:

  • Workflow: text-to-video, image-to-video, reference-to-video, or video-to-video.
  • Subject and environment.
  • One primary visible action per shot.
  • Camera framing, movement, and pace.
  • Duration and aspect ratio when known.
  • The role of every @Image, @Video, or @Audio reference.
  • Identity, product geometry, composition, motion, timing, or audio that must remain stable.
  • Delivery goal: product clip, cinematic beat, social post, transition, loop, or sequence.

Never invent model-specific controls, limits, input support, prices, or availability. Use the current product interface as the source of truth when exact settings matter.

Build the prompt

Write in this order:

  1. Subject and scene.
  2. One visible action.
  3. Camera framing and one motivated camera move.
  4. Lighting and visual treatment.
  5. Duration and aspect ratio if confirmed.
  6. Reference roles and continuity constraints.
  7. A short artifact-focused avoid list.

Prefer observable instructions over abstract mood. Keep subject motion separate from camera motion. Avoid simultaneous competing actions, contradictory camera commands, and long style lists.

For image-to-video, preserve identity, layout, lighting direction, and geometry unless transformation is requested. For reference-to-video, keep every token exactly as supplied and assign one clear role per reference. For video-to-video, state which source motion, timing, camera path, and scene structure must survive.

Write in the user's language unless another language is requested. Never translate, renumber, or remove @Image1, @Video1, or @Audio1-style tokens.

Plan sequences

Give every shot one purpose and one action. Include timing, framing, subject action, applicable reference role, continuity anchor, and intended end frame. Use the previous shot's final frame as the next visual anchor. Preserve screen direction, identity, wardrobe or product geometry, and lighting unless a deliberate transition changes them.

Debug one axis at a time

Revise in this order:

  1. Subject action or motion intensity.
  2. Framing or camera path.
  3. Reference roles and continuity constraints.
  4. Lighting or style language.

Translate vague failures into observable corrections. Reduce competing instructions before adding detail.

Use the optional MCP

When MCP tools are available:

  • build_video_prompt creates a structured prompt pack.
  • plan_reference_sequence creates a 1–6 shot plan.
  • diagnose_video_prompt identifies missing controls.
  • get_seevido_resources returns canonical site resources.

Connect the stdio server with:

openclaw mcp add seevido \
  --command npx \
  --arg -y \
  --arg github:gpt-img-2/seevido-prompt-mcp \
  --include 'build_video_prompt,plan_reference_sequence,diagnose_video_prompt,get_seevido_resources'

Then run openclaw mcp doctor seevido --probe. If the installed OpenClaw release does not expose the mcp command group, add npx -y github:gpt-img-2/seevido-prompt-mcp as a Stdio server in its MCP settings.

The MCP is optional. If unavailable, apply the same workflow manually and do not imply that a tool ran.

Return a compact deliverable

For one shot, return Prompt, optional Reference roles, Continuity constraints, Avoid, and one Revision move. For sequences, return a numbered shot plan followed by shared continuity rules and one assembly note.

Canonical resources