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wan-2-7万 2 7

Agent Skill

wan-2-7 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。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。

总安装

288

周安装

12

GitHub Stars

公开资料未说明

下载量

96
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:wan-2-7(万 2 7)
来源仓库:https://github.com/kalvinrv/wan-2-7
安装命令:
openclaw skills install wan-2-7
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 wan-2-7

简介

wan-2-7 在 RunComfy 上使用 Wan 2.7 模型生成文本到视频。

  • 适合在 OpenClaw 中制作动画或视频剪辑时使用。
  • 支持音频驱动和多参考调节功能。wan-2-7 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 安装前需确认权限范围、维护状态及是否会触发 GPU 资源调用。
  • 适用于视频创作者探索 AI 生成内容技术。

SKILL.md

name
wan-2-7
displayName
🫧 Wan 2.7 — Pro Pack on RunComfy
description
>
emoji
🫧
homepage
https://www.runcomfy.com
license
MIT
clawdis
requires
bins
env
config

🫧 Wan 2.7 — Pro Pack on RunComfy

runcomfy.com · docs · Text-to-video

Wan-AI's Wan 2.7 — flagship video model with multi-reference conditioning and audio-driven lip-sync — hosted on the RunComfy Model API.

When to pick this model (vs siblings)

You wantUse
Lip-sync video to an audio track you supplyWan 2.7 ✓ (audio_url)
Multi-reference fine motion controlWan 2.7
Smooth transitions, accurate motion physicsWan 2.7
Currently-#1 blind-vote video modelHappyHorse 1.0
Multi-modal cinematic with image+video+audio refs + in-pass voice generationSeedance 2.0 Pro
Cinematic motion editing on existing footageKling Video O1
Ultra-fast iterationLTX 2

If the user said "Wan" / "Wan 2.7" / "wan-ai" / "alibaba video" explicitly, route here regardless.

Prerequisites

  1. RunComfy CLInpm i -g @runcomfy/cli
  2. RunComfy accountruncomfy login opens a browser device-code flow.
  3. CI / containers — set RUNCOMFY_TOKEN=<token> instead of runcomfy login.

Endpoints + input schema

wan-ai/wan-2-7/text-to-video

FieldTypeRequiredDefaultNotes
promptstringyesUp to ~5000 chars / ~1500 tokens.
audio_urlstringnoWAV/MP3, 3–30s, ≤15MB. Drives lip-sync. Omit → background music auto-generated.
aspect_ratioenumno16:916:9, 9:16, 1:1, 4:3, 3:4.
resolutionenumno1080p720p or 1080p.
durationenumno52–15 (whole seconds).
negative_promptstringnoUp to 500 chars. Concrete issues to avoid.
enable_prompt_expansionboolnotrueAuto-rewrites short prompts. Disable for literal control.
seedintno0..2^31-1. Reuse for variants.

How to invoke

Default (5s 1080p 16:9, prompt-expanded):

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{"prompt": "<user prompt>"}' \
  --output-dir <absolute/path>

Audio-driven lip-sync (your own track):

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{
    "prompt": "Medium close-up of the spokesperson, warm key light, locked tripod, slight breathing motion.",
    "audio_url": "https://.../voiceover.mp3",
    "duration": 12,
    "aspect_ratio": "9:16"
  }' \
  --output-dir <absolute/path>

Literal control (no auto-expansion):

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{
    "prompt": "<exactly what you want, verbatim>",
    "enable_prompt_expansion": false,
    "negative_prompt": "no subtitles, no flicker, no distorted hands"
  }' \
  --output-dir <absolute/path>

Prompting — what actually works

Camera + motion in plain English. "Slow dolly in", "locked tripod, low angle", "handheld follow", "crane move from above". Front-load the shot.

One primary action per clip. Don't pile up multiple competing actions. Pick the beat: "she turns, then smiles" not "she turns AND smiles AND a bus passes AND...".

Use negative_prompt for concrete issues. Good: "no subtitles, no watermark, no flicker". Bad (vague): "no bad lighting".

Prompt expansion is on by default. Short prompts get auto-rewritten by the model. For terse / literal prompts (e.g. brand-strict ad copy), disable with enable_prompt_expansion: false.

Audio specs matter. audio_url must be 3–30s, ≤15MB, WAV/MP3. Out-of-range files reject. Match audio length to clip duration.

Iterate seeds. Reuse the same seed when you want consistent output across variants of the same prompt. Change seed for genuine variety.

Anti-patterns:

  • Static-frame descriptions → motion will be vague.
  • Vague negatives ("no bad colors") → ignored.
  • Audio outside the 3–30s / 15MB / WAV-MP3 spec → rejected.
  • Prompts > 5000 chars / 1500 tokens → degraded output.

Where it shines

Use caseWhy Wan 2.7
Lip-synced ads with custom voiceoveraudio_url accepts your track
Multi-language dub variantsSame prompt, different audio_url per language
Multi-reference motion controlUp to 5 reference media (image / video / voice)
Smooth transitions + motion physicsStrong physics-aware motion priors
Negative-prompted clean outputTargeted issue exclusion

Sample prompts (verified to produce strong results)

Page example (product showcase):

Cinematic medium shot of a product on a marble surface, soft studio
lighting, slow subtle camera push-in, shallow depth of field, premium
commercial look, crisp 1080p detail

Lip-synced spokesperson (with audio_url):

Medium close-up of a confident spokesperson in a softly-lit recording
booth, leaning slightly toward the camera, locked tripod, shallow depth
of field, warm key light from camera-left.

Vertical platform-native:

9:16 vertical short. A barista pulls a single espresso shot, steam
rising into morning sun, rich crema slowly forming. Close-up handheld,
shallow DOF, warm cafe ambience.

Limitations

  • Duration cap 15s. For longer narratives, stitch multiple calls.
  • No native 4K — 1080p ceiling.
  • Aspect ratios — only the 5 documented values.
  • Audio specs — 3–30s, ≤15MB, WAV/MP3 only.
  • Reference media cap 5 (image + video + voice combined).
  • For in-pass voice generation (no separate audio track), use Seedance 2.0 Pro — Wan accepts audio rather than generating it.

Exit codes

codemeaning
0success
64bad CLI args
65bad input JSON / schema mismatch
69upstream 5xx
75retryable: timeout / 429
77not signed in or token rejected

Full reference: docs.runcomfy.com/cli/troubleshooting.

How it works

The skill invokes runcomfy run wan-ai/wan-2-7/text-to-video with a JSON body matching the schema. The CLI POSTs to https://model-api.runcomfy.net/v1/models/wan-ai/wan-2-7/text-to-video, polls the request, fetches the result, and downloads any .runcomfy.net/.runcomfy.com URL into --output-dir. Ctrl-C cancels the remote request before exit.

Security & Privacy

  • Token storage: runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner-only read/write). Set RUNCOMFY_TOKEN env var to bypass the file entirely in CI / containers.
  • Input boundary: the user prompt is passed as a JSON string to the CLI via --input. The CLI does NOT shell-expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content.
  • Third-party content: image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image-based prompt injection is a known risk for any image-edit / video-edit model.
  • Outbound endpoints: only model-api.runcomfy.net (request submission) and *.runcomfy.net / *.runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks.
  • Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a malicious or runaway model output.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.71%
按下载量换算73

安全审计

VirusTotal

通过

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通过

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通过

权限和风险

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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