Token导航 LogoToken导航

Agent Skill · 开发

giggle-generation-video(咯咯笑一代视频)

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。

giggle-generation-video 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,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 12,289。

总安装 1,350周安装 58GitHub Stars 公开资料未说明下载 473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
unknown

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:giggle-generation-video(咯咯笑一代视频)
来源仓库:https://github.com/giggle-official/skills
仓库路径:skills/giggle-generation-video
安装命令:
npx skills add https://github.com/giggle-official/skills --skill giggle-generation-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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/giggle-official/skills --skill giggle-generation-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。

giggle-generation-video 用于辅助视频生成和动画合成,适合组织镜头或维护 Remotion 项目。适用于脚本化剪辑、渲染问题排查或视频素材合成的场景。通过 npx skills add 命令从指定 GitHub 仓库安装使用。使用时需确认分辨率、时长和导出格式,涉及外部素材时应核对版权授权要求。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/giggle-generation-video

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/giggle-official/skills --skill giggle-generati…;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

giggle-generation-video 怎么安装?

在终端执行 npx skills add https://github.com/giggle-official/skills --skill giggle-generation-video。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

giggle-generation-video 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

giggle-generation-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。

giggle-generation-video 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

giggle-generation-video 用的人多吗?

公开数据是累计安装 1,350 次,近一周安装 58 次,下载 473 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。

giggle-generation-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

  • 同时适配 4 种工具,换客户端不用重新找替代品。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,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。
  • 需要明确授权才能用到公司项目里的场景。
  • 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
giggle-generation-video

咯咯笑一代视频 · 本页

1,350—接触敏感数据未明确有提醒

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

Giggle Video Generation

Source: giggle-official/skills · API: giggle.pro

Generates AI videos via giggle.pro's Generation API. Supports text-to-video and image-to-video. Submit task → agent proactively polls with --query until done (see Continuous progress updates). No Cron, no file writes—all operations via exec.


Installation Requirements

RequirementValue
Binarypython3
EnvironmentGIGGLE_API_KEY (required; see below)
Piprequests

Where to get GIGGLE_API_KEY: Open giggle.pro while logged in → left sidebar → API Key (API 密钥) → create or copy your key. Then export GIGGLE_API_KEY=your_api_key. The script will prompt if not configured.

No Retry on Error: If script execution encounters an error, do not retry. Report the error to the user directly and stop.

Supported Models

ModelSupported Durations (s)DefaultDescription
grok6, 106Strong overall capability, recommended
grok-fast6, 106grok fast version
sora24, 8, 124OpenAI Sora 2
sora2-pro4, 8, 124Sora 2 Pro
sora2-fast10, 1510Sora 2 Fast
sora2-pro-fast10, 1510Sora 2 Pro Fast
kling255, 105Kling video model
seedance15-pro4, 8, 124Seedance Pro (with audio)
seedance15-pro-no-audio4, 8, 124Seedance Pro (no audio)
veo314, 6, 84Google Veo 3.1 (with audio)
veo31-no-audio4, 6, 84Google Veo 3.1 (no audio)
minimax2366MiniMax model
wan255, 100Wanxiang model

Note: --duration must be chosen from the model's supported durations, otherwise the API will error.


Frame Reference (Image-to-Video)

For image-to-video, --start-frame and --end-frame support three mutually exclusive formats:

MethodFormatExample
asset_idasset_id:<ID>asset_id:lkllv0yv81
urlurl:<URL>url:https://example.com/img.jpg
base64base64:<DATA>base64:iVBORw0KGgo...

Each frame parameter can only use one of these methods.


Execution Flow: Submit and Query

Video generation is asynchronous (typically 60–300 seconds). Submit a task to get task_id, then query until the task reaches a terminal state. All commands run via exec; API key from system env.


Continuous progress updates (default; user need not put this in their prompt)

Video jobs are usually ~1–5+ minutes (sometimes longer). The user does not need to ask you to check progress.

  1. Right after submit, say you submitted, give task_id, and give a realistic wait range for the model/load (not a generic “1–3 minutes” if the pipeline is often slower).
  2. Poll proactively: run --query about every 15–30 seconds until a terminal state—do not wait for the user to ask.
  3. After each query, briefly report status in natural language; if stdout is non-terminal JSON (processing, etc.), paraphrase and say you will check again—do not go silent.
  4. When done: forward full signed video links on success; explain failures clearly. If still non-terminal after ~20 minutes (adjust if the user/model context suggests longer is normal), stop blind polling, explain, keep task_id, and suggest retry or a later manual check.
  5. If the user explicitly opts out of polling (“don’t poll”, “I’ll ask”), submit once, give task_id, and only --query when they ask.

Step 1: Submit Task

First send a message to the user: Video generation is submitted; you will query progress on a schedule and report updates—no need to nag. Include task_id once you have it from the JSON response.

# Text-to-video (default grok-fast)
python3 scripts/generation_api.py \
  --prompt "Camera slowly pushes forward, person smiling in frame" \
  --model grok-fast --duration 6 \
  --aspect-ratio 16:9 --resolution 720p

# Image-to-video - use asset_id as start frame
python3 scripts/generation_api.py \
  --prompt "Person slowly turns around" \
  --start-frame "asset_id:lkllv0yv81" \
  --model grok-fast --duration 6 \
  --aspect-ratio 16:9 --resolution 720p

# Image-to-video - use URL as start frame
python3 scripts/generation_api.py \
  --prompt "Scenery from still to motion" \
  --start-frame "url:https://example.com/img.jpg" \
  --model grok-fast --duration 6

# Image-to-video - both start and end frame
python3 scripts/generation_api.py \
  --prompt "Scene transition" \
  --start-frame "asset_id:abc123" \
  --end-frame "url:https://example.com/end.jpg" \
  --model grok --duration 6

Response example:

{"status": "started", "task_id": "55bf24ca-e92a-4d9b-a172-8f585a7c5969"}

Store task_id in memory (addMemory):

giggle-generation-video task_id: xxx (submitted: YYYY-MM-DD HH:mm)

Step 2: Query Until Done (default: proactive polling)

After each submit for the current task, repeatedly run (every ~15–30s until terminal state or timeout), without waiting for the user to ask:

python3 scripts/generation_api.py --query --task-id <task_id>

Between queries, use a short sleep (e.g. 15–30 seconds) in the shell, or separate tool invocations with delay—do not go silent; summarize each result to the user.

Output handling:

stdout patternAction
Plain text with video links (e.g. ready message)Forward to user as-is; stop polling this task
Plain text with errorForward to user as-is; stop polling this task
JSON {"status": "processing", "task_id": "..."} (or similar non-terminal)Tell user current status + that you will check again shortly; continue polling per this section

If the user asks about progress while you are already polling, answer with the latest known status (run an extra --query if needed).

Link return rule: Video links in results must be full signed URLs (with Policy, Key-Pair-Id, Signature query params). Do not strip response-content-disposition=attachment when the API returns it; forward as-is (script only encodes ~ → %7E).


New Request vs Query Old Task

When the user initiates a new video generation request, must run Step 1 to submit a new task. Do not reuse old task_id from memory.

For the in-flight task, use proactive polling as above. For an older task (user refers to a previous video / previous task_id), query that task_id when they ask, or poll it if they want continuous updates on that specific task.


Parameter Reference

ParameterDefaultDescription
--promptrequiredVideo description prompt
--modelgrokSee "Supported Models" table
--durationmodel defaultMust choose from model's supported durations
--aspect-ratio16:916:9, 9:16, 1:1, 3:4, 4:3
--resolution720p480p, 720p, 1080p
--start-frame-Image-to-video start frame: asset_id:ID, url:URL, or base64:DATA
--end-frame-Image-to-video end frame, same format as start

Note: base64 parameter supports base64-encoded images. Pass the raw Base64 string directly, do not add the data:image/xxx;base64, prefix.


Interaction Guide

When the user request is vague, guide per the steps below. If the user has provided enough info, run the command directly.

Step 1: Model Selection (required)

Before generating, must introduce available models and let the user choose. Display the model list from "Supported Models" table. Wait for explicit user choice before continuing.

Step 2: Video Duration

For the chosen model, show supported duration options. Default to the model's default duration.

Step 3: Generation Mode

Question: "Do you need reference images as start/end frame?"
Options: No - text-to-video only / Yes - image-to-video (set start/end frame)

Step 4: Aspect Ratio

Question: "What aspect ratio do you need?"
Options: 16:9 - Landscape (recommended) / 9:16 - Portrait / 1:1 - Square

Step 5: Execute and Display

Follow the flow: send message → Step 1 submit → Step 2 proactive polling until a terminal state, with a short user-facing update after each query. Forward exec stdout to the user as-is where appropriate (especially final links and errors).

平台分布

Codex

34.51%
按下载量换算163

Claude

32.84%
按下载量换算155

Cursor

17.85%
按下载量换算84

Gemini CLI

9.43%
按下载量换算45

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。

继续浏览同类 Skills