Home › Skills › 视频生成 通义万相 Wan 2.7
Developer Tools

视频生成 通义万相 Wan 2.7 skill for OpenClaw

⬇ 4.1K downloads ★ 0 stars Version 1.3.23 Rank #1967 of 10,000+

What this skill does

Tongyi Wanxiang 2.7 video model 鈥?one model covers text-to-video, first/last-frame-to-video, and reference-to-video.

The 视频生成 通义万相 Wan 2.7 skill is part of the Developer Tools category — developer tools that help your agent write, review, debug, and ship code. You can install it on its own or alongside other developer tools skills from the OpenClaw catalog.

The 视频生成 通义万相 Wan 2.7 skill is ranked #1967 by downloads in the OpenClaw skill catalog (4.1K total downloads, 0 stars). It belongs to the Developer Tools category alongside 3540 other top-10000 skills.

How to install the 视频生成 通义万相 Wan 2.7 skill

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

  1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
  2. Open the in-app Skills panel.
  3. Search for dlazy-wan2-7 and click Install.
  4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add the 视频生成 通义万相 Wan 2.7 skill with a single command:

openclaw skills add dlazy-wan2-7

This pulls dlazy-wan2-7 from ClawHub and installs it into ~/.openclaw/skills/dlazy-wan2-7/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use the 视频生成 通义万相 Wan 2.7 skill

Once installed, the 视频生成 通义万相 Wan 2.7 skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Turning video into a finished short

视频生成 通义万相 Wan 2.7 works with video. Getting from there to something postable is a separate job: ViralMint — an open-source video pipeline — reframes to vertical, cleans the audio, cuts dead air, burns animated captions, and exports a version sized for TikTok, Reels, and Shorts.

It runs as an MCP server, so an OpenClaw agent can drive it from the same chat you already use: ask for a short, and the render comes back finished. See how to connect a video pipeline to your agent.

Manual install (advanced)

If you prefer manual installation:

  1. Click the Download skill .zip button above to grab dlazy-wan2-7-1.3.23.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/dlazy-wan2-7/ (create the directory if it does not exist).
  3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install 视频生成 通义万相 Wan 2.7?

Install 视频生成 通义万相 Wan 2.7 in the OpenClaw Easy desktop app by opening the Skills panel, searching for dlazy-wan2-7, and clicking Install. From a terminal you can run: openclaw skills add dlazy-wan2-7. Either way the skill is placed in ~/.openclaw/skills/dlazy-wan2-7/.

Is the 视频生成 通义万相 Wan 2.7 skill free?

Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.

What does 视频生成 通义万相 Wan 2.7 do?

Tongyi Wanxiang 2.7 video model 鈥?one model covers text-to-video, first/last-frame-to-video, and reference-to-video.

Related: more developer tools skills

If the 视频生成 通义万相 Wan 2.7 skill looks useful, you may also want to check out other developer tools skills in the OpenClaw catalog:

Skills in this catalog are community-contributed integrations published on ClawHub and distributed under their own open-source licences. Product and company names, and any third-party service a skill connects to, are trademarks of their respective owners; a listing here does not imply affiliation with, sponsorship by, or endorsement from them. This page does not distribute any third-party application. Rights holders can reach us at hello@openclaw-easy.com.

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Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models