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Agent Skill · 效率

miniature-build-video(微型搭建视频)

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

miniature-build-video 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 13,630。

总安装 3,648周安装 149GitHub Stars 公开资料未说明下载 1,180核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.5

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:miniature-build-video(微型搭建视频)
来源仓库:https://github.com/zoucdr/miniature-build-video
安装命令:
openclaw skills install miniature-build-video
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install miniature-build-video

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

miniature-build-video 生成垂直微型构建短片,支持文本转镜头与灯光效果渲染。适用于产品展示、建筑漫游或创意视频制作,提供沉浸式视觉体验。可结合 Remotion 框架定制合成逻辑,输出高分辨率短视频素材。

安装命令:openclaw skills install miniature-build-video;需指定分辨率与时长参数。涉及人物或品牌素材时应核查版权授权,商业用途需额外确认合规边界。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install miniature-build-video;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

miniature-build-video 怎么安装?

在终端执行 openclaw skills install miniature-build-video。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

miniature-build-video 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

miniature-build-video 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

miniature-build-video 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

miniature-build-video 用的人多吗?

公开数据是累计安装 3,648 次,近一周安装 149 次,下载 1,180 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

miniature-build-video 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
miniature-build-video

微型搭建视频 · 本页

3,648—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
miniature-build-video
version
1.0.2
description
Generate vertical miniature build & reveal shorts (WeryAI): text or finished-shot image to shallow-depth push-ins, lights coming on, immersive camera. Use when you need a miniature diorama reel, tilt-shift room clip, or the user asks for a tiny house lights-on moment or a slow push into interior detail. Requires WERYAI_API_KEY at runtime (declared in frontmatter for registries). SEO: miniature build video; miniature model build video generation.
tags
[craft, miniature, immersive, creative, aesthetic, short-video]
requires
{ env: ["WERYAI_API_KEY"] }
metadata
openclaw
emoji
🏗️
primaryEnv
WERYAI_API_KEY
paid
true
network_required
true
requires
env
bins
node
>=18
user-invocable
true

Miniature build & diorama video generation

Late night: a matchbox-sized Japanese konbini glows amber; the camera eases out of darkness toward it—bokeh swallows the world while the glass door, shelves, and tiny fluorescents stay sharp. That “small but real” immersion is the emotional hook this skill targets.

Conbini, rainy noodle stand, cyberpunk workshop—or a photo of a finished build: one line or one image → clip.

Dependencies: WERYAI_API_KEY + Node.js 18+. When you run the CLI, scripts/video_gen.js must exist; WERYAI_VIDEO_API.md must exist under resources/ (supply both via publish or pre-use assembly). Full commands and JSON fields: see resources/WERYAI_VIDEO_API.md. No other Cursor skills. Default parameters and model tiers are in the tables below; live API limits follow weryai models. Before installing or running, review the bundled video_gen.js to confirm it meets your requirements. Pay particular attention to how it handles local files if you choose to allow their usage, ensuring this behavior aligns with the skill's intended workflow for image-to-video requests.

Registry metadata: The only required runtime secret is WERYAI_API_KEY. It appears in YAML frontmatter as top-level requires.env (flow mapping, for tools that flatten root keys only), metadata.openclaw.primaryEnv, and metadata.openclaw.requires.env. Skill directories and registries should surface that requirement up front so installers see it before download. Never commit the key inside the package.

Before you install or set WERYAI_API_KEY

  1. Trust: Confirm you trust WeryAI and accept that prompts and image inputs (URLs and, if used, uploaded bytes) are sent to WeryAI’s servers over the network.
  2. Sensitive content: Do not put secrets in prompt. Do not supply image URLs or local files you consider sensitive unless you accept provider-side processing.
  3. --dry-run first: Run node scripts/video_gen.js wait --json '…' --dry-run (and/or submit-* with --dry-run) before setting a key to inspect the JSON shape; WERYAI_API_KEY is not required for --dry-run only (see WERYAI_VIDEO_API.md).
  4. Source: If you cannot verify the package author or need strict data control, do not set WERYAI_API_KEY, or run only in an isolated / test environment.

Environment variables (bundled video_gen.js)

  • Required for real API calls: WERYAI_API_KEY only (models, generation, status, local-image upload). Not required for --dry-run only.
  • Not read by this script: Environment variables do not override API hostnames; https://api.weryai.com and https://api-growth-agent.weryai.com are fixed in code (see Security). Do not expect URL-override knobs—there are none in this build.
  • Polling: wait uses fixed exponential backoff and timeout constants in the script (see WERYAI_VIDEO_API.md), not separate poll env vars in this package.

Script vs skill defaults (must match JSON)

  • model: The CLI has no built-in default model. If model is missing or empty in JSON, video_gen.js returns MISSING_PARAM (no default model). This skill’s recommended default in tables is KLING_V3_0_PRO—always pass "model":"<confirmed key>" explicitly in wait / submit-* JSON so it matches the pre-submit table.
  • resolution: For KLING_V3_0_PRO (this skill’s default tier), omit resolution entirely from JSON—sending it can cause 1002 / parameter errors for models that do not support that field. Only add resolution when the chosen model lists it in node scripts/video_gen.js models and your confirmation table explicitly includes it.

Prerequisites

  • WERYAI_API_KEY must be set in the environment before running video_gen.js.
  • Node.js 18+ is required. Prefer public https image URLs. If the assembled scripts/video_gen.js supports local file paths, review and verify the script first, then get explicit consent before it reads a local image and uploads it to WeryAI to obtain a public URL.
  • Each successful wait run consumes WeryAI credits; re-running creates new paid tasks.

Security, secrets, and API hosts

  • WERYAI_API_KEY: Treat as a secret. Only configure it if you trust this skill's source; it is listed in OpenClaw metadata as requires.env / primaryEnv so installers know it is mandatory at runtime (never commit it inside the skill package).
  • API hosts (fixed in video_gen.js): Video tasks use https://api.weryai.com; the models list uses https://api-growth-agent.weryai.com. The bundled script pins these bases in code—only WERYAI_API_KEY is read from the environment for authentication. Do not rely on any environment variables to change API hostnames; requests only go to those official endpoints plus the documented upload URL when a local image is uploaded (see WERYAI_VIDEO_API.md).
  • Local image handling disclosure: Prefer public https image URLs. If the assembled scripts/video_gen.js supports local file paths, it may read a local image and upload it to WeryAI to obtain a public URL; require review / verification and explicit consent before using that path.
  • Remote processing: Paid runs send prompt and image inputs to WeryAI; see ## Before you install or set WERYAI_API_KEY.
  • Higher assurance: Follow ## Before you install or set WERYAI_API_KEY; use a short-lived or isolated environment for paid runs; review scripts/video_gen.js (HTTPS submit + poll loop) before production use. Verify whether the runtime can read local image files and upload them to WeryAI, and obtain explicit consent before using that path.

Prompt expansion (mandatory)

video_gen.js does not expand prompts. Before every wait --json, turn the user's short or vague brief into a full English production prompt.

When: The user gives only keywords, one line, or loose intent—or asks for richer video language. Exception: They paste a finished long prompt within the model's prompt_length_limit and ask you not to rewrite; still show the full text in the confirmation table.

Always add (video language): shot scale and angle; camera move or lock-off; light quality and motivation; subject action paced to duration; one clear payoff for this niche; state 9:16 vertical when this skill defaults to vertical.

Length: Obey prompt_length_limit for the chosen model_key when this doc lists it; trim filler adjectives before removing core action, lens, or light clauses.

Confirmation: The pre-submit table must include the full expanded prompt (never a one-line summary). Wait for confirm or edits.

Niche checklist

  • Miniature world: shallow DOF, practical warm lights, dolly/push-in reveal; diorama or room-in-a-box.
  • Beats: build → paint → lights on or vehicle pass; cozy atmosphere, tactile materials.
  • Scale cues: matchstick, coin, or fingertip references where useful.

### Example prompts at the top of this file are short triggers only—always expand from the user's actual request.

Workflow

  1. Confirm the user request matches this skill's scenario (text-to-video and/or image-to-video as documented).
  2. Collect the user's brief, optional image URL(s), tier (best / good / fast) or an explicit model key.
  3. Expand prompt (mandatory): Unless the user supplied a finished long prompt and explicitly asked not to rewrite it, expand the brief into a full English production prompt using ## Prompt expansion (mandatory) below. Do not call the API with only the user's minimal words.
  4. Check the expanded prompt against the selected model's prompt_length_limit in the frozen tables in this document (when present); shorten if needed.
  5. Verify duration, aspect_ratio, generate_audio, negative_prompt, and other fields against the frozen tables in this document and WERYAI_VIDEO_API.md. Include resolution only when the selected model supports it (for this skill’s default KLING tier, do not send resolution—see ## Script vs skill defaults).
  6. Show the pre-submit parameter table including the full expanded prompt; wait for confirm or edits.
  7. After confirmation, run node scripts/video_gen.js wait --json '...' with the expanded prompt.
  8. Parse stdout JSON and return video URLs; on failure, surface errorCode / errorMessage and suggest parameter fixes.

CLI reference

node scripts/video_gen.js wait --json '{"model":"…","prompt":"…","duration":5,"aspect_ratio":"9:16"}'
node scripts/video_gen.js wait --json '…' --dry-run
node scripts/video_gen.js status --task-id <id>

Full reference: WERYAI_VIDEO_API.md.

Definition of done

Done when the user receives at least one playable video URL from the API response, or a clear failure explanation with next steps. All parameters used must fall within the selected model's allowed sets in this document. The submitted prompt must be the expanded production prompt unless the user explicitly supplied a finished long prompt and asked not to rewrite it.

Boundaries (out of scope)

  • Does not review platform compliance, copyright, or portrait rights; does not guarantee commercial usability of outputs.
  • Does not provide non-WeryAI offline rendering, traditional edit timelines, or API field combinations not documented in this SKILL or WERYAI_VIDEO_API.md.
  • Do not link to weryai-model-capabilities.md or shared ../references/ paths; use resources/WERYAI_VIDEO_API.md for CLI/API details.
  • Does not hard-code absolute paths in the skill doc; run node scripts/... from the skill package root (the directory containing SKILL.md) so scripts/ and resources/ paths resolve.

Example prompts

  • Hand-built miniature café: final beat lights on inside, warm fill, slow push vertical
  • Use this street diorama still: tiny car passes, shop windows light up
  • Painted model on base, rotate reveal, ultra-shallow depth of field
  • Miniature build reveal 9:16, cozy warm lights turning on inside tiny house

Default parameters

FieldValue
ModelKLING_V3_0_PRO (must appear as "model" in JSON—the script does not default it)
Aspect ratio9:16 (fixed vertical)
DurationShort (duration: 5); use 10 for a longer build pass
ResolutionOmit for KLING default (do not include the key in JSON)
StyleVery shallow DOF, believable materials, accent light on hero props, slow push or subtle orbit (fixed)
AudioOn (room tone + tiny prop detail for immersion)
API validity (default KLING_V3_0_PRO): Text-to-video duration only 5 / 10 / 15; aspect_ratio only 9:16, 1:1, 16:9. Image-to-video aspect_ratio only 9:16, 16:9, 1:1. No resolution field—do not send it. For fast tier with VEO: text-to-video VEO_3_1_FAST, image-to-video CHATBOT_VEO_3_1_FAST, with duration fixed at 8, aspect_ratio only 9:16 or 16:9. When switching model_key, follow the allowed sets in this section’s model/API constraints and the API validity note above; do not send resolution to models that do not support it.

Scene description → miniature world

Purpose: Concrete scene ideas, fast visual tests, or batching mood variants—no physical model required.

Inputs:

Scene type (konbini / kitchen / cottage / corner stall / workshop / cyber set) and mood (warm healing / neon cyber / daylight / rainy amber). If mood is omitted, pick the lighting that usually performs for that scene. Optionally stress build process vs finished tour.

Extract key props and light, pick an angle that triggers “I want this,” build the prompt, show full parameters, wait for confirm, then node scripts/video_gen.js wait --json '…'.

Full parameters are shown before generation; wait for confirmation.

Parameter configuration:

FieldValue
modelKLING_V3_0_PRO
aspect_ratio9:16
duration5
generate_audiotrue
resolution*(omit—do not send for this model)*

Example inputs:

“Japanese konbini at night, warm healing” → the skill builds:

Extreme close-up macro shot at eye level, a palm-sized miniature Japanese convenience store diorama on a dark surface, warm amber interior light glows through tiny sliding glass doors and frostwork windows illuminating a perfectly detailed interior — miniature shelves stocked with thumb-sized product packages, a tiny register counter, a softbox ceiling panel. The camera dollies in very slowly at 30fps toward the entrance as if walking toward it, the shallow depth of field keeps only the storefront razor-sharp while the surrounding darkness melts away. Cold blue night-time ambient fills the exterior, creating a warm-cold color split at the door threshold. ASMR soft ambient hum, distant city night sound, faint interior muzak.

“Cyberpunk workshop, neon” →

Medium close-up at 45-degree overhead angle, a miniature cyberpunk studio diorama the size of a shoebox — crammed with tiny glowing monitors, cable-draped desk, neon-lit bookshelves in pink and cyan, a miniature action figure at the keyboard. The camera orbits slowly around the scene at 60fps in a single smooth rotation, neon light refracts off every tiny reflective surface — monitor bezels, coffee mug, glossy floor tile. Volumetric light rays from the neon tubes create a soft haze above the scene. Deep black void background isolates the diorama completely. ASMR low electronic hum, faint keyboard clicks, ambient synth drone.

“Hand-build a log cabin from scratch, full process” →

Close-up tracking shot over a clean white work mat, precise hands assemble a miniature log cabin frame piece by piece in time-lapse — wooden strips cut, glued, pressed together, roof tiles laid row by row, a tiny front door hung on micro hinges. Final sequence returns to real time 60fps: a hand places the last roof tile, steps back, and a small warm interior light switches on inside the finished cabin, its glow spilling through two windows onto the mat. Neutral overhead workshop light throughout, shallow depth of field isolates the build in progress from surrounding tools. ASMR wood snapping, glue applicator, the soft click of the interior light turning on.
Note: More specific beats (palette, hero prop, time of day) track intent better. “Konbini” vs “late-night warm konbini push toward glass door” are different pictures.

Model photo → immersive motion

Purpose: Finished physical model or reference still → camera motion for posts or archive.

Inputs:

Image URL (public HTTPS). Optional motion direction:

  • Slow push in: From outside toward interior or front—depth emphasis
  • Lights on: Dark to lit, sources coming up in sequence
  • Orbit: Slow 360-style pass around the build

Default pick: if already bright inside → push; if dark → lights-on.

Read scene, existing light, and hero props; match motion; show parameters; confirm; node scripts/video_gen.js wait --json '…'.

Full parameters are shown before generation; wait for confirmation.

Parameter configuration:

FieldValue
modelKLING_V3_0_PRO
aspect_ratio9:16
duration5
generate_audiotrue
resolution*(omit—do not send for this model)*
imageUser-supplied image URL

Example:

“This is my cyber street build, orbit it https://...” →

Starting from the miniature diorama in the image, the camera performs a slow smooth 180-degree orbital rotation around the scene at 30fps, each angle revealing new details of the model — signage, light sources, material textures. Shallow depth of field maintains focus on the nearest model surface throughout the rotation, blurring the far side into bokeh. The existing lighting in the image is preserved and enhanced with subtle lens flare at bright neon sources. ASMR ambient city soundscape matching the scene aesthetic.
Note: Prefer public https URLs; login-gated or in-app-only links may fail. If the assembled scripts/video_gen.js supports local file paths, review/verify the script and explicitly consent before local read-and-upload to WeryAI. Clearer, more centered photos track camera motion better.

Prompt keyword cheat sheet

  • Immersion: shallow depth of field bokeh background, only the miniature in sharp focus, diorama isolated on dark surface
  • Light: warm amber spill light, neon volumetric haze, cold-warm color contrast at threshold, interior light switching on
  • Camera: slow dolly push-in, smooth orbital rotation, static locked-off reveal, gradual light fade-in
  • Materials: visible wood grain texture, reflective tiny surface, thumb-sized detail props, micro scale furniture
  • Emotion: inviting glow, tiny world feeling, perfectly scaled details, a world you could step into

平台分布

OpenClaw

70.81%
按下载量换算836

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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