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Agent Skill · 开发

life-hack-video(生活黑客视频)

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。

life-hack-video 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 6,494。

总安装 4,633周安装 195GitHub Stars 公开资料未说明下载 1,622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
0.1.0

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:life-hack-video(生活黑客视频)
来源仓库:https://github.com/zoucdr/life-hack-video
安装命令:
openclaw skills install life-hack-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 life-hack-video

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

生成垂直领域生活技巧演示短片,适配短视频平台传播。覆盖清洁、收纳、小工具等实用场景的快速展示。life-hack-video 属于开发类 Skill,可作为该场景下的辅助能力补充。输出脚本与素材清单,配合 WeryAI 生成最终成片。涉及人物肖像或品牌露出时需注意版权与授权合规。

视频分辨率与时长受平台限制,请提前确认规格要求。

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 life-hack-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

life-hack-video 怎么安装?

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

life-hack-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。

life-hack-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。

life-hack-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。

life-hack-video 用的人多吗?

公开数据是累计安装 4,633 次,近一周安装 195 次,下载 1,622 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。

life-hack-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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
life-hack-video

生活黑客视频 · 本页

4,633—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
life-hack-video
version
1.0.0
description
Generate vertical life-hack / gadget demo shorts (WeryAI): problem—tool—one-move payoff; stains, prep, storage, quick fixes. Use when you need a life hack demo reel, gadget seeding clip, or the user asks for a cat demoing a lint roller or 3-second grease removal. SEO: life hack video; life hack gadget demo video generation.
tags
[practical, gadgets, life-hacks, seeding, efficiency, short-video]
metadata
{ "openclaw": { "emoji": "💡", "primaryEnv": "WERYAI_API_KEY", "paid": true, "network_required": true, "requires": { "env": ["WERYAI_API_KEY"], "bins": ["node"], "node": ">=18" } } }
user-invocable
true

Life hack & gadget demo video generation

A cat clears carpet hair in three seconds—before/after in one frame. That “pain → fix” beat is the core of hack content. Anthropomorphic stars (cat / bunny / bear) show real-looking tool use; the shorter the arc from problem to solved, the better. One line can be enough.

Dependencies: scripts/video_gen.js in this directory + WERYAI_API_KEY + Node.js 18+. No dependency on other Cursor skills.

Prerequisites

  • WERYAI_API_KEY must be set in the environment before running video_gen.js.
  • Node.js 18+ is required. Image inputs must be public https URLs (no local file paths).
  • 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. Only WERYAI_API_KEY is read from the environment—do not rely on URL-related environment variables.
  • Higher assurance: Run generation in a short-lived or isolated environment (separate account or container), and review scripts/video_gen.js (HTTPS submit + poll loop) before production use.

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

  • Demo clarity: hands + product + step order in one vertical read; bright practical light; quick legible motion.
  • Hook: problem → hack motion → result in frame; platform-native pacing for short vertical.
  • Background: clean desk, kitchen counter, or neutral—avoid clutter that fights the hack.

### 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, resolution, generate_audio, negative_prompt, and other fields against the frozen tables and API notes in this SKILL.md.
  6. Show the pre-submit parameter table including the full expanded prompt; wait for confirm or edits.
  7. After confirmation, run node {baseDir}/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 {baseDir}/scripts/video_gen.js wait --json '{"model":"…","prompt":"…","duration":5,"aspect_ratio":"9:16"}'
node {baseDir}/scripts/video_gen.js wait --json '…' --dry-run
node {baseDir}/scripts/video_gen.js status --task-id <id>

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 here.
  • Does not hard-code absolute paths in the skill doc; {baseDir} means the skill package root (same level as SKILL.md).

Example prompts

  • Carpet covered in cat hair; lint roller one pass clean; cat as hero; full story in 5s vertical
  • Use this greasy stove image: spray, wipe, shine motion
  • Mandoline demo: before/after should feel exaggerated but believable
  • Life hack gadget demo 9:16, problem then one-move solution

Default parameters

FieldValue
ModelKLING_V3_0_PRO
Aspect ratio9:16 (fixed vertical)
Duration5 seconds (duration: 5—problem → fix inside five seconds)
AudioOff
Visual styleClose or medium; natural home light; tool + problem object in frame; clear before/after; crisp motion
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.

Gadget fixes everyday pain

High-share formula: pain shot first → tool hero insert → clean decisive use → pristine after. One sentence on pain + tool; the prompt fills the arc.

The user should provide:

  • Character (cat / bunny / bear / custom)
  • Pain scene (carpet fur / cable mess / hard-to-cut food / rusty screw / specific home pain)
  • Tool (e.g. lint roller, mandoline, cable clips—be specific)

Generation flow:

  1. Collect character, pain, tool; ask for look and motion if vague.
  2. Three-beat prompt: messy / hard → tool entrance (hero moment) → clean / easy result.
  3. Show defaults and wait:

You must show all parameters in a table and wait for explicit user confirmation before submitting:

> 📋 Ready to generate—please confirm: > > | Parameter | This run | Notes | > |-----------|----------|-------| > | model | KLING_V3_0_PRO | Best default; fast: text VEO_3_1_FAST, image CHATBOT_VEO_3_1_FAST (duration 8); good → KLING_V3_0_STA; or name a model | > | aspect_ratio | 9:16 | Default KLING: 9:16, 1:1, 16:9 | > | duration | 5s | KLING: 5 / 10 / 15; VEO fast: 8 only | > | generate_audio | false | Whether to auto-generate audio | > | prompt | Full expanded English prompt (entire text for this run) | Revise before confirm | > | Loop seam | No | Reply “loop” for seamless loop | > > Reply “confirm” to start, or list what to change.

  1. After confirmation ({baseDir} is skill root):
   node {baseDir}/scripts/video_gen.js wait --json '{"model":"(model from confirmation table)","prompt":"(full English prompt)","aspect_ratio":"9:16","duration":5,"generate_audio":true}'

Match table to JSON; add resolution only if supported. Parse stdout videos.

Parameter configuration:

FieldValue
modelKLING_V3_0_PRO
aspect_ratio9:16
duration5
generate_audiofalse

Expanded prompt: Compose at generation time per ## Prompt expansion (mandatory) from the user's actual brief—do not reuse fixed sample paragraphs.

Expected outcome: Problem → fix inside 5s; utility reads without captions; after visibly cleaner than before—strong seeding feel.


Twist: unexpected uses

Not the “normal” use—the “wait, it can do *that*?” angle. Often outperforms straight demos.

Name tool + surprise use; generate:

Parameters are shown before generation; wait for confirmation before submit.

Expanded prompt: Compose at generation time per ## Prompt expansion (mandatory) from the user's actual brief—do not reuse fixed sample paragraphs.


Prompt story structure

Problem (first ~3s): mess is visible and clearly defined, the problem is immediately legible, close-up emphasizes the scale of the issue

Tool entrance: the tool enters frame from above, hero product presented front and center, satisfying unboxing or pick-up moment

Fix beat: single action produces immediate visible result, one stroke cleans the entire surface, problem disappears in real time, satisfying transformation in one motion

Result frame: after is dramatically cleaner than before, same angle before-and-after comparison, solution is obvious without words

Tip: The worst failure is not knowing *what* got fixed. Lead with 1–2 sentences on the problem state, then the tool—order matters. before-after in continuous shot reads more narrative than describing two isolated states.

平台分布

OpenClaw

94.62%
按下载量换算1,535

安全审计

VirusTotal

通过

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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