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Agent Skill · 效率

dpp-pipeline(dpp 管道)

dpp-pipeline 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。

dpp-pipeline 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,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 17,870。

总安装 2,496周安装 112GitHub Stars 公开资料未说明下载 808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
1.0.2

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:dpp-pipeline(dpp 管道)
来源仓库:https://github.com/kotot/dpp-pipeline
安装命令:
openclaw skills install dpp-pipeline
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 dpp-pipeline

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。

将本地源视频与产品图合成为植入式营销视频。适用于电商产品展示与广告素材制作。dpp-pipeline 属于效率类 Skill,可作为该场景下的辅助能力补充。支持自动化流程减少手动剪辑工作量。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。使用前需准备符合尺寸要求的源文件。

注意版权归属,确保所用素材拥有合法使用权。

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 dpp-pipeline;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

dpp-pipeline 怎么安装?

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

dpp-pipeline 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。

dpp-pipeline 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。

dpp-pipeline 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。

dpp-pipeline 用的人多吗?

公开数据是累计安装 2,496 次,近一周安装 112 次,下载 808 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。

dpp-pipeline 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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
dpp-pipeline

dpp 管道 · 本页

2,496—接触敏感数据MIT-0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

name
dpp-pipeline
description
Use when you need to turn a local source video and one product image into a single-product placement video with the DPP pipeline.
license
UNLICENSED
allowed-tools
Bash Read Glob Grep
metadata
openclaw
version
0.1.0
primaryEnv
ARK_API_KEY
user-invocable
true
compatibility
Requires Python 3.11+, ffmpeg, network access, Ark credentials, and optional TOS credentials when compose-best must auto-upload reference media. Reads and writes in the caller workspace or DPP_WORKDIR.
requires
env
bins

DPP Pipeline

Run the DPP storyboard, placement, and compose-best flow from a local workspace.

The skill bundles its Python runtime under runtime/, but it does not treat the installed skill directory as the project workspace. Inputs and outputs live under the caller's current working directory by default. Override that with DPP_WORKDIR when needed.

When to Use

  • Generate storyboard.json from a local video with dpp-storyboard.
  • Generate a single-product material config from one product image under assets/.
  • Select the best storyboard segment for one product image with dpp-placement.
  • Run the final best-segment composition flow with dpp-compose-best.
  • Replace the best segment in the original video with the generated clip using dpp-final-cut.

Do not use this skill for multi-product batch processing. This skill handles one local video and one product image at a time.

Dependencies

  • Python 3.11+
  • ffmpeg
  • Network access to Ark and TOS
  • Ark environment variables in the target workspace .env
  • TOS_BUCKET, TOS_AK, TOS_SK, TOS_ENDPOINT, and TOS_REGION when compose-best must auto-upload the reference clip or image
  • TOS_OBJECT_PREFIX, TOS_ENABLE_HTTPS, and TOS_FORCE_ENDPOINT are optional TOS tuning variables

Install Python dependencies by running:

scripts/bootstrap_runtime.sh

Workspace Layout

The runtime lives inside the installed skill. The caller workspace holds inputs, configs, logs, and outputs:

<workspace>/
  .env
  assets/
    <single product image>
  video/
    demo.mp4
  configs/
    placement_material.json
  log/
  output/
    <video_stem>/
      finalCut/

Initialize a new workspace with:

scripts/init_workspace.sh

That command creates assets/, video/, configs/, and output/, and copies sample files into place.

Workflow

  1. Run scripts/bootstrap_runtime.sh.
  2. If the target workspace is empty, run scripts/init_workspace.sh.
  3. Ensure the workspace .env contains Ark credentials and defaults.
  4. Ensure video/demo.mp4 exists before storyboard, unless the user will pass --video.
  5. Ensure assets/ contains exactly one product image before material generation, unless the user will pass --image.
  6. Run scripts/run_storyboard.sh.
  7. Run scripts/run_generate_material.sh.
  8. Run scripts/run_placement.sh.
  9. Run scripts/run_compose_best.sh.
  10. Run scripts/run_final_cut.sh.

Do not skip stage ordering unless the user explicitly asks to reuse an existing artifact.

Review Pauses

Do not pause by default.

  • If the user wants review pauses, stop after each requested stage and report the artifact path.
  • If the user asks to continue, move directly to the next stage when the required inputs already exist.
  • If the user asks to rerun a later stage, reuse earlier artifacts unless the input changed.

Typical checkpoints:

  • After storyboard: review segmentation quality and thumbnail coverage.
  • After placement: review best_segment_index, ranking, and placement rationale.
  • After compose-best: review composition_result.json, prompt quality, and reference-media URL status.
  • After final-cut: review finalcut_result.json and verify the output video at output/<video_stem>/finalCut/final_cut.mp4.

Execution Rules

  • Run the stage scripts from the caller workspace, or set DPP_WORKDIR to the target workspace path.
  • Keep the installed skill directory immutable except for .venv/ and the generated runtime/ bundle.
  • Always bootstrap the runtime before the first stage command.
  • dpp-storyboard, dpp-placement, and dpp-compose-best can each take more than 10 minutes. Do not assume the process is hung just because it is quiet for a while; warn the user that the stage is long-running and let it complete naturally.
  • After each stage, report the main artifact path.
  • Before compose-best auto-upload, verify TOS_BUCKET, TOS_AK, TOS_SK, TOS_ENDPOINT, and TOS_REGION if the user did not provide --reference-video-url or DPP_REFERENCE_VIDEO_URL.
  • This skill sends prompts and media metadata to Ark. Compose-best may also upload the reference clip and product image to TOS.

Detailed commands live in references/commands.md.

Scripts

  • scripts/bootstrap_runtime.sh
  • scripts/init_workspace.sh
  • scripts/run_storyboard.sh
  • scripts/run_generate_material.sh
  • scripts/run_placement.sh
  • scripts/run_compose_best.sh
  • scripts/run_final_cut.sh

Each script forwards all CLI arguments to the underlying Python module.

平台分布

OpenClaw

72.59%
按下载量换算587

安全审计

VirusTotal

未展示

ClawScan

通过

Static analysis

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。目前只有一个公开来源,建议同时核对源仓库。

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