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Aliyun Wan R2v

作者 cinience · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install aliyun-wan-r2v
功能描述
Use when generating reference-based videos with Alibaba Cloud Model Studio Wan R2V models (wan2.6-r2v-flash, wan2.6-r2v). Use when creating multi-shot videos...
使用说明 (SKILL.md)

Category: provider

Model Studio Wan R2V

Validation

mkdir -p output/aliyun-wan-r2v
python -m py_compile skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py && echo "py_compile_ok" > output/aliyun-wan-r2v/validate.txt

Pass criteria: command exits 0 and output/aliyun-wan-r2v/validate.txt is generated.

Output And Evidence

  • Save reference input metadata, request payloads, and task outputs in output/aliyun-wan-r2v/.
  • Keep at least one polling result snapshot.

Use Wan R2V for reference-to-video generation. This is different from i2v (single image to video).

Critical model names

Use one of these exact model strings:

  • wan2.6-r2v-flash
  • wan2.6-r2v

Newer official releases may prefer the flash variant for lower latency and lower cost.

Prerequisites

  • Install SDK in a virtual environment:
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
  • Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Normalized interface (video.generate_reference)

Request

  • prompt (string, required)
  • reference_video (string | bytes, required)
  • reference_image (string | bytes, optional)
  • duration (number, optional)
  • fps (number, optional)
  • size (string, optional)
  • seed (int, optional)

Response

  • video_url (string)
  • task_id (string, when async)
  • request_id (string)

Async handling

  • Prefer async submission for production traffic.
  • Poll task result with 15-20s intervals.
  • Stop polling when SUCCEEDED or terminal failure status is returned.

Local helper script

Prepare a normalized request JSON and validate response schema:

.venv/bin/python skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py \
  --prompt "Generate a short montage with consistent character style" \
  --reference-video "https://example.com/reference.mp4"

Output location

  • Default output: output/aliyun-wan-r2v/videos/
  • Override base dir with OUTPUT_DIR.

Workflow

  1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
  2. Run one minimal read-only query first to verify connectivity and permissions.
  3. Execute the target operation with explicit parameters and bounded scope.
  4. Verify results and save output/evidence files.

References

  • references/sources.md
安全使用建议
This skill appears to implement what it claims (a helper for Alibaba Wan R2V), but the instructions and manifest don't match in a few places. Before installing or running it: 1) Do not blindly export credentials — create a least-privilege DASHSCOPE_API_KEY for testing. 2) Verify the 'dashscope' package is the official SDK (check PyPI and vendor docs). 3) Fix/check paths in SKILL.md: the validation command references a different path than the actual script, and the script's default output dir differs from the SKILL.md output locations; run the helper script manually with explicit paths to ensure it behaves as expected. 4) Run in an isolated environment (venv or container) and inspect the helper script (it is small and only builds/validates JSON). If those mismatches are corrected, the skill is coherent; until then treat the package as suspicious due to documentation/manifest inconsistencies.
功能分析
Type: OpenClaw Skill Name: aliyun-wan-r2v Version: 1.0.0 The skill bundle is a legitimate integration for Alibaba Cloud's Wan R2V video generation models. The Python script (scripts/prepare_r2v_request.py) is a simple utility for formatting JSON requests, and the instructions in SKILL.md correctly guide the agent through environment setup and API usage without any signs of malicious intent, data exfiltration, or unauthorized execution.
能力评估
Purpose & Capability
Name/description, SKILL.md content, and the helper script all align with an Alibaba Cloud Model Studio Wan R2V integration (request preparation, polling guidance, recommended model names). The included prepare_r2v_request.py is small and matches the stated purpose.
Instruction Scope
SKILL.md instructs creating a venv, installing the 'dashscope' SDK, and setting DASHSCOPE_API_KEY or adding dashscope_api_key to ~/.alibabacloud/credentials — but the skill metadata lists no required env vars. Validation steps and output paths in SKILL.md reference 'skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py' and 'output/aliyun-wan-r2v/', while the repo files live at 'scripts/prepare_r2v_request.py' and the helper script writes to 'output/ai-video-wan-r2v/'. These path mismatches mean the provided validation commands may fail and indicate sloppiness in instructions. Aside from these inconsistencies, the instructions don't request unrelated files or unexpected external endpoints.
Install Mechanism
There is no formal install spec (instruction-only). The SKILL.md recommends pip installing 'dashscope' inside a venv; this is an expected approach for using an SDK but the package origin isn't validated in the skill. Instruction-only skills are lower risk than downloaded/executed archives, but you should confirm 'dashscope' is the official Alibaba SDK before installing.
Credentials
SKILL.md requires DASHSCOPE_API_KEY or credentials in ~/.alibabacloud/credentials but the skill manifest declares no required environment variables or primary credential. Asking for an API key for the provider is reasonable for the described functionality, but the omission from metadata is an inconsistency that could confuse users and automated permission checks.
Persistence & Privilege
The skill is not always-enabled and does not request system-wide changes. It does write request/response artifacts to an output directory (as described), which is reasonable for a provider integration.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install aliyun-wan-r2v
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /aliyun-wan-r2v 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of aliyun-wan-r2v skill for generating reference-based videos using Alibaba Cloud Model Studio Wan R2V models. - Supports multi-shot video creation from reference videos/images, preserving character style. - Provides validation steps and output handling guidance, including evidence and polling snapshots. - Documents required model names (`wan2.6-r2v-flash`, `wan2.6-r2v`), with preference for “flash” when available. - Outlines normalized interface for video generation, request/response schema, and async handling best practices. - Includes setup instructions, helper scripts, and workflow recommendations for reliable operation.
元数据
Slug aliyun-wan-r2v
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Aliyun Wan R2v 是什么?

Use when generating reference-based videos with Alibaba Cloud Model Studio Wan R2V models (wan2.6-r2v-flash, wan2.6-r2v). Use when creating multi-shot videos... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。

如何安装 Aliyun Wan R2v?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install aliyun-wan-r2v」即可一键安装,无需额外配置。

Aliyun Wan R2v 是免费的吗?

是的,Aliyun Wan R2v 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Aliyun Wan R2v 支持哪些平台?

Aliyun Wan R2v 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Aliyun Wan R2v?

由 cinience(@cinience)开发并维护,当前版本 v1.0.0。

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