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Agent Skill · 效率

media-generation(媒体一代)

media-generation 用于处理图像、截图、视觉识别或图片素材相关工作,适合在 OpenClaw 中需要让 Agent 分析图片、整理视觉素材或辅助图像流程时使用。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。

media-generation 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;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 5,941。

总安装 10,074周安装 424GitHub Stars 公开资料未说明下载 3,528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
2.2.0

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:media-generation(媒体一代)
来源仓库:https://github.com/lijiazhen0623/media-generation
安装命令:
openclaw skills install media-generation
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 media-generation

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。

media-generation 处理图像生成与编辑任务。支持短视频制作、修复及对象中心编辑。可参考图像输入进行批量素材生产。适用于视觉内容创作全流程辅助。安装时按仓库提供的命令执行,建议先在测试环境验证依赖、命令权限和文件改动范围。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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 media-generation;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

    它需要需要联网,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

media-generation 怎么安装?

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

media-generation 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。

media-generation 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

media-generation 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。

media-generation 用的人多吗?

公开数据是累计安装 10,074 次,近一周安装 424 次,下载 3,528 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。

media-generation 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

  • 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

  • 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
media-generation

媒体一代 · 本页

10,074—需要联网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
media-generation
description
Generate images, edit existing images, create short videos, run inpainting/outpainting and object-focused edits, use reference images as provider inputs, batch related media jobs from a manifest, and fetch returned media from URLs/HTML/JSON/data URLs/base64. Use when working on AI image generation, AI image editing, mask-based inpainting, outpainting, reference-image workflows, short AI video generation, product-shot variations, or reusable media-production pipelines.

Media Generation

Handle image generation, image editing, and short video generation through one workflow: choose the right modality, pass caller intent through to the provider, save outputs under tmp/images/ or tmp/videos/, and prefer the bundled helpers over ad-hoc one-off API calls.

Workflow decision

  • If the user wants a brand-new still image, use an image-generation model.
  • If the user supplies an image or wants a specific existing image changed, use an image-edit workflow.
  • If the user wants motion / a clip / a short video, use a video-generation model.
  • If the request includes one or more reference images, use the helper that supports reference-image transport.

Standard workflow

  1. Determine whether the task is image generation, image editing, or video generation.
  2. Clarify only when required to execute the request correctly.
  3. Prefer scripts/generate_image.py for still-image generation.
  4. Prefer scripts/edit_image.py for direct image edits.
  5. Prefer scripts/mask_inpaint.py for localized edits with masks or generated regions.
  6. Prefer scripts/outpaint_image.py for canvas expansion / outpainting.
  7. Prefer scripts/reference_media.py when reference images need to be passed through.
  8. Prefer scripts/generate_video.py for video generation, especially when the provider may return async job payloads.
  9. Prefer scripts/generate_batch_media.py for repeatable batch jobs, templated variations, or auditable manifests.
  10. Prefer scripts/object_select_edit.py for simple object-vs-background edits on transparent assets or clean backdrops.
  11. If the provider returns a URL, path, HTML snippet, markdown snippet, data: URL, or b64_json, use scripts/fetch_generated_media.py.
  12. Save outputs under:

- images → tmp/images/ - videos → tmp/videos/

  1. If the user wants files sent in chat, prefer sending the local downloaded file.
  2. Keep the original remote reference as fallback when local retrieval fails.

Prompt handling

Default to prompt pass-through.

  • Pass the caller's prompt through unchanged.
  • Use optional request fields only when the caller provides them.
  • Keep prompt semantics under caller control.

Use the scripts mainly as functional helpers:

  • normalize arguments
  • map fields to provider-specific JSON
  • upload files
  • poll async jobs
  • download returned media
  • save outputs under tmp/images/ or tmp/videos/

Delivery rules

  • Save generated or edited images in tmp/images/.
  • Save generated videos in tmp/videos/.
  • Never scatter generated files in the workspace root.
  • If message delivery blocks remote URLs, download locally first and then send the local file.
  • If a remote file cannot be fetched locally but the raw link may still help, provide the original link clearly.

Helper quick guide

Use the smallest helper that matches the request:

  • scripts/generate_image.py → direct still-image generation
  • scripts/edit_image.py → direct full-image edits
  • scripts/mask_inpaint.py → localized edits with an explicit or generated mask
  • scripts/outpaint_image.py → canvas expansion before an edit call
  • scripts/reference_media.py → reference-image transport and delegation
  • scripts/generate_consistent_media.py → backward-compatible wrapper only
  • scripts/generate_batch_media.py → repeatable manifest-driven batches
  • scripts/object_select_edit.py → simple object-vs-background edits on transparent or clean-backdrop assets
  • scripts/generate_video.py → direct video generation and async polling
  • scripts/fetch_generated_media.py → normalize returned media refs into local files

Use references/model-capabilities.md when deciding which helper fits the modality, transport, or return shape. Use references/reference-image-workflow.md for reference-image transport details. Use references/batch-workflows.md for manifest structure and batch execution behavior.

Minimal examples:

python3 skills/media-generation/scripts/generate_image.py \
  --prompt 'person' \
  --size '1024x1024' \
  --out-dir 'tmp/images' \
  --prefix 'generated'

python3 skills/media-generation/scripts/edit_image.py \
  --image 'tmp/images/source.jpg' \
  --prompt 'replace the background' \
  --out-dir 'tmp/images' \
  --prefix 'edited'

python3 skills/media-generation/scripts/mask_inpaint.py \
  --image 'tmp/images/source.jpg' \
  --x 120 --y 80 --width 220 --height 180 \
  --prompt 'replace the masked area' \
  --out-dir 'tmp/images' \
  --prefix 'mask-result'

python3 skills/media-generation/scripts/outpaint_image.py \
  --image 'tmp/images/source.jpg' \
  --left 512 --right 512 --top 128 --bottom 128 \
  --mode blur \
  --prompt 'extend outward' \
  --out-dir 'tmp/images' \
  --prefix 'outpaint-result'

python3 skills/media-generation/scripts/reference_media.py \
  --mode image \
  --reference-image 'tmp/images/reference.png' \
  --prompt 'character' \
  --size '1024x1024' \
  --out-dir 'tmp/images' \
  --prefix 'reference-output'

python3 skills/media-generation/scripts/generate_batch_media.py \
  --manifest 'tmp/images/media-batch.jsonl' \
  --vars-json '{"subject":"item"}' \
  --summary-out 'tmp/images/media-batch-summary.json' \
  --continue-on-error \
  --print-json

python3 skills/media-generation/scripts/object_select_edit.py \
  --image 'tmp/images/product.png' \
  --selection-mode alpha \
  --edit-target background \
  --prompt 'replace the background' \
  --out-dir 'tmp/images' \
  --prefix 'product-bg-edit'

python3 skills/media-generation/scripts/generate_video.py \
  --prompt 'motion clip' \
  --size '720x1280' \
  --seconds 6 \
  --out-dir 'tmp/videos' \
  --prefix 'generated-video'

Quick compatibility checklist

Before blaming the skill, check these first:

  • config exists and is valid JSON
  • config.models.providers.<provider> exists
  • the selected provider has both baseUrl and apiKey
  • the chosen endpoint actually exists on that provider
  • the chosen model name is valid for that endpoint
  • any provider-specific fields passed through --extra-json or --extra-json-file match that provider's schema

Defaults used by the bundled scripts:

  • config path: ~/.openclaw/openclaw.json or $OPENCLAW_CONFIG
  • default provider: $OPENCLAW_MEDIA_PROVIDER, otherwise the first provider found in config
  • default model names: placeholders unless overridden by env vars or --model

- image → $OPENCLAW_MEDIA_IMAGE_MODEL or image-model - edit → $OPENCLAW_MEDIA_EDIT_MODEL or image-edit-model - video → $OPENCLAW_MEDIA_VIDEO_MODEL or video-model

  • output root: tmp/ or $MEDIA_GENERATION_OUTPUT_ROOT
  • output paths are resolved relative to the current working directory unless you pass an absolute --out-dir

Quick troubleshooting

Common failure patterns:

  • provider not found → pass --provider explicitly or set $OPENCLAW_MEDIA_PROVIDER
  • placeholder model warning (image-model / image-edit-model / video-model) → pass --model explicitly or set the matching $OPENCLAW_MEDIA_*_MODEL env var
  • config not found / invalid JSON → pass --config explicitly or fix the OpenClaw config file
  • HTTP 404 → check --endpoint and video polling paths
  • HTTP 400 → check model name and provider-specific payload fields in --extra-json / --extra-json-file
  • HTTP 401/403 → check the provider apiKey
  • request failed before HTTP response → check base URL, proxy/TLS, or network reachability
  • video accepted then failed later → check request payload, provider logs, or switch provider/model

Use --print-json when debugging so the response body, resolved endpoint, and failure hints stay visible.

References

Read these selectively:

  • helper selection, modality fit, transport notes, return-shape handling → references/model-capabilities.md
  • reference-image transport rules and compatibility notes → references/reference-image-workflow.md
  • manifest format, templating, and batch execution behavior → references/batch-workflows.md

Primary helpers:

  • image generation → scripts/generate_image.py
  • image edit → scripts/edit_image.py
  • mask inpaint → scripts/mask_inpaint.py
  • outpaint → scripts/outpaint_image.py
  • reference-image transport → scripts/reference_media.py
  • backward-compatible wrapper → scripts/generate_consistent_media.py
  • video generation → scripts/generate_video.py
  • batch generation → scripts/generate_batch_media.py
  • object-select edit → scripts/object_select_edit.py
  • object mask prep → scripts/prepare_object_mask.py
  • shared request utility → scripts/media_request_common.py
  • smoke tests → scripts/smoke_test.py
  • media retrieval → scripts/fetch_generated_media.py

平台分布

OpenClaw

82.25%
按下载量换算2,902

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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