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Agent Skill · 研究检索

ultimate-ai-media-generator-skill(终极 AI 媒体生成器技能)

ultimate-ai-media-generator-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ultimate-ai-media-generator-skill 是研究检索类 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,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 36,669。

总安装 1,885周安装 77GitHub Stars 41下载 610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:ultimate-ai-media-generator-skill(终极 AI 媒体生成器技能)
来源仓库:https://github.com/zerolu/ultimate-ai-media-generator-skill
仓库路径:skills/ultimate-ai-media-generator-skill
安装命令:
npx skills add https://github.com/zerolu/ultimate-ai-media-generator-skill --skill ultimate-ai-media-generator-skill
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/zerolu/ultimate-ai-media-generator-skill --skill ultimate-ai-media-generator-skill

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。ultimate-ai-media-generator-skill 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态。注意是否会触发联网或文件读写操作。

来源仓库内路径:skills/ultimate-ai-media-generator-skill

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/zerolu/ultimate-ai-media-generator-skill --ski…;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

ultimate-ai-media-generator-skill 怎么安装?

在终端执行 npx skills add https://github.com/zerolu/ultimate-ai-media-generator-skill --skill ultimat…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ultimate-ai-media-generator-skill 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。

ultimate-ai-media-generator-skill 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。

ultimate-ai-media-generator-skill 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。

ultimate-ai-media-generator-skill 用的人多吗?

公开数据是累计安装 1,885 次,近一周安装 77 次,下载 610 次,GitHub 41 星。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。

ultimate-ai-media-generator-skill 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ultimate-ai-media-generator-skill

终极 AI 媒体生成器技能 · 本页

1,88541接触敏感数据未明确未通过

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

Ultimate-AI-Media-Generator-Skill

Overview

Use this skill to call CyberBara APIs reliably, create image/video generation tasks, and return final media URLs with credit-aware flow.

Implementation Architecture

The runtime uses a layered Python architecture:

  • scripts/cyberbara_api.py: thin entrypoint only
  • src/cyberbara_cli/cli.py: command parsing and command routing
  • src/cyberbara_cli/usecases/: flow orchestration (generation + polling)
  • src/cyberbara_cli/policies/: safety and policy rules (credits quote + formal confirmation)
  • src/cyberbara_cli/gateways/: raw CyberBara API client
  • src/cyberbara_cli/config.py: API key discovery and local persistence
  • src/cyberbara_cli/constants.py: fixed base URL and shared constants

When extending behavior, keep business rules in usecases/ or policies/, not in scripts/.

Set Up Runtime Inputs

The script uses fixed base URL:

https://cyberbara.com

API key lookup order:

  1. --api-key
  2. environment variable CYBERBARA_API_KEY
  3. local cache file ~/.config/cyberbara/api_key
  4. interactive prompt (if running in terminal)

Recommended one-time setup command:

python3 scripts/cyberbara_api.py setup-api-key "<api-key>"

Or save from environment variable:

export CYBERBARA_API_KEY="<api-key>"
python3 scripts/cyberbara_api.py setup-api-key --from-env

If API key is missing, the script immediately asks for it and shows where to get one:

https://cyberbara.com/settings/apikeys

When you provide API key via --api-key or interactive prompt, it is saved to:

~/.config/cyberbara/api_key

Future runs reuse this cached key, so users do not need to provide it every time.

Run The Standard Generation Flow

  1. Discover available models.
  2. Upload reference images when task scene needs image inputs.
  3. Quote credits before creating a generation task.
  4. Create image or video generation task and wait for final output.
  5. Automatically save generated media locally and open it.
  6. Check usage records when needed.

Reference commands:

# 1) List video models
python3 scripts/cyberbara_api.py models --media-type video

# 2) Upload local reference images
python3 scripts/cyberbara_api.py upload-images ./frame.png ./style.jpg

# 3) Estimate credits
python3 scripts/cyberbara_api.py quote --json '{
  "model":"sora-2",
  "media_type":"video",
  "scene":"text-to-video",
  "options":{"duration":"10"}
}'

# 4) Create a video task (default behavior: wait for success, save outputs to ./media_outputs, auto-open)
python3 scripts/cyberbara_api.py generate-video --json '{
  "model":"sora-2",
  "prompt":"A calm drone shot over snowy mountains at sunrise",
  "scene":"text-to-video",
  "options":{"duration":"10","resolution":"standard"}
}'

# 5) Existing task: wait + save/open outputs
python3 scripts/cyberbara_api.py wait --task-id <TASK_ID> --interval 5 --timeout 900

Image and video generation are confirmation-gated by default:

# Single image request: script auto-quotes, then asks you to type CONFIRM
python3 scripts/cyberbara_api.py generate-image --json '{
  "model":"nano-banana-pro",
  "prompt":"A cinematic portrait under neon rain",
  "scene":"text-to-image",
  "options":{"resolution":"1k"}
}'

# Batch image requests (JSON array): script auto-quotes each request and prints total estimated credits
python3 scripts/cyberbara_api.py generate-image --file ./image-requests.json

image-requests.json format:

[
  {
    "model": "nano-banana-pro",
    "prompt": "A cinematic portrait under neon rain",
    "scene": "text-to-image",
    "options": { "resolution": "1k" }
  },
  {
    "model": "nano-banana-pro",
    "prompt": "A product still life with dramatic side light",
    "scene": "text-to-image",
    "options": { "resolution": "1k" }
  }
]

Only use --yes after explicit user approval has been obtained:

python3 scripts/cyberbara_api.py generate-image --file ./image-requests.json --yes
python3 scripts/cyberbara_api.py generate-video --json '{
  "model":"sora-2",
  "prompt":"A calm drone shot over snowy mountains at sunrise",
  "scene":"text-to-video",
  "options":{"duration":"10","resolution":"standard"}
}' --yes

Control auto-save and open behavior:

# keep waiting but do not auto-open media
python3 scripts/cyberbara_api.py generate-image --file ./image-requests.json --yes --no-open

# custom output directory
python3 scripts/cyberbara_api.py generate-video --json '{...}' --yes --output-dir ./downloads

# submit only (no wait/save/open)
python3 scripts/cyberbara_api.py generate-video --json '{...}' --yes --async

Use Script Capabilities

scripts/cyberbara_api.py supports:

  • setup-api-key to persist API key into local cache
  • models to list public models (--media-type image|video optional)
  • upload-images to upload local image files to /api/v1/uploads/images
  • quote to estimate credit cost from JSON request body
  • generate-image to auto-quote credits, compute total for batch requests, require formal confirmation, create task(s), wait, then save/open outputs
  • generate-video to auto-quote credits, compute total for batch requests, require formal confirmation, create task(s), wait, then save/open outputs
  • task to fetch task snapshot by task ID
  • wait to poll task until success, failed, or canceled, then save/open outputs
  • balance and usage to inspect credits
  • raw for direct custom endpoint calls

Use --file request.json instead of --json for long payloads.

Enforce API Payload Rules

  • Send auth via API key (Authorization: Bearer <key> or x-api-key).
  • Send public request fields under options.* only.
  • Prefer explicit scene to avoid inference ambiguity.
  • Include options.image_input for image-to-image and image-to-video.
  • Include options.video_input for video-to-video.
  • Poll /api/v1/tasks/{taskId} until final status; only success guarantees output URLs.
  • Before every image or video generation submission, obtain quote first and get explicit user confirmation.
  • For multiple image/video requests, calculate and present total estimated credits before submission.
  • Save output files under media_outputs/ by default and auto-open them unless disabled.

Navigate Detailed Model Options

Use the reference file for full model matrices and examples:

  • references/cyberbara-api-reference.mdx

For fast lookup in large reference:

rg '^## |^### ' references/cyberbara-api-reference.mdx
rg 'kling-2.6|sora-2|veo-3.1|seedance' references/cyberbara-api-reference.mdx

Handle Common Failures

  • invalid_api_key or api_key_required: verify key and headers.
  • insufficient_credits: quote first or recharge credits.
  • invalid_scene or scene_not_supported: choose scene supported by model.
  • invalid_request: verify prompt and options requirements by model.
  • task_not_found: verify task ID and environment domain.

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

平台分布

Codex

35.91%
按下载量换算219

Claude

29.18%
按下载量换算178

Cursor

19.17%
按下载量换算117

Gemini CLI

9.88%
按下载量换算60

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

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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