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在 OpenClaw 中安装
/install lrshuai-image-to-video
功能描述
参考生视频技能。当你需要提供一张图片和文本描述来生成视频时调用此技能。
使用说明 (SKILL.md)
Image to Video (参考生视频)
CRITICAL INSTRUCTION FOR AGENT:
当用户要求调用 lrshuAI-image-to-video 技能时,你绝对不能使用 openclaw run。你必须直接通过系统自带的 python 命令来运行 script/invoke_model.py。
支持的模型
此技能包含支持单张图片和文本生成视频的模型。
- Veo 3.1 (
veo_3_1): 高质量视频生成模型。 - Sora 2 (
sora-2): 通用高质量视频生成模型。 - Kling V3 (
kling-v3): 可灵 V3 视频生成模型。 - Kling V3 Omni (
kling-v3-omni): 可灵 Omni 视频模型。 - Vidu I2V ViduQ2 (
vidu-i2v-viduq2): Vidu 图生视频模型。 - Jimeng OmniHuman 1.5 (
jimeng-omnihuman-1_5): 即梦数字人视频生成。 - Bailian Wan2 6 R2V (
bailian-wan2_6-r2v): 阿里百炼 Wan2 视频生成。 - Bailian Wan2 6 R2V Flash (
bailian-wan2_6-r2v-flash): 阿里百炼 Wan2 视频生成(极速版)。
调用示例
python script/invoke_model.py --model 'veo_3_1' --prompt '镜头平移,画面中的人物开始微笑' --image 'path/to/image.jpg'
安全使用建议
This skill appears to implement an image→video call to a remote model API, but there are two things you should verify before installing or supplying credentials: 1) The SKILL.md forces the agent to run the bundled script via the system python and explicitly tells it not to use the platform runner — that can bypass platform monitoring or safety controls. 2) The script will send your TEAM_API_KEY and any provided local images/videos (base64-encoded) to a default endpoint (https://dlazy.com/api/ai/tool) unless you override TEAM_BASE_URL. TEAM_BASE_URL is not declared in the skill metadata. Actionable suggestions: do not provide a real TEAM_API_KEY unless you trust the endpoint; ask the publisher for provenance/homepage and to declare TEAM_BASE_URL in metadata; request the SKILL.md be changed to allow using the platform runner (or explain why it must be bypassed); inspect network activity in an isolated environment if you test it; avoid sending sensitive images to unknown third parties. If you cannot verify the endpoint or the publisher, mark this skill untrusted.
功能分析
Type: OpenClaw Skill
Name: lrshuai-image-to-video
Version: 1.0.2
The skill contains a 'CRITICAL INSTRUCTION' in SKILL.md that explicitly commands the AI agent to bypass the standard 'openclaw run' execution path, insisting on direct system execution via 'python'. The script 'script/invoke_model.py' collects the 'TEAM_API_KEY' and local media files, transmitting them to an external endpoint (https://dlazy.com/api/ai/tool). While this behavior aligns with the stated purpose of image-to-video generation, the forceful instruction to circumvent the platform's standard runner and the transmission of credentials to a third-party domain are high-risk indicators.
能力评估
Purpose & Capability
The skill's name/description, required binary (python), and the script's behavior (upload image/video + prompt to an AI model endpoint) are consistent with an image-to-video generator. However the script defaults to an external domain (https://dlazy.com/api/ai/tool) as the backend and the skill has no homepage or provenance information; that default endpoint is not documented in the metadata and may be surprising to users.
Instruction Scope
SKILL.md contains a strong, explicit instruction that the agent must run `python script/invoke_model.py` directly and must not use `openclaw run`. That directive looks intended to bypass platform tooling/wrappers (telemetry, sandboxing, or VM-level controls). The script itself reads local image/video files (base64-encodes them) and will transmit them to the remote API — expected for this purpose but potentially sensitive. The SKILL.md / systemPrompt enforces runtime behavior that reduces oversight, which is a red flag.
Install Mechanism
No install spec is present (instruction-only plus a bundled script). Nothing is downloaded or written at install time by the registry metadata. The only runtime requirement is python. This is low install mechanism risk.
Credentials
The declared required env var is TEAM_API_KEY (primary credential), which is reasonable for an external model API. However the script also reads TEAM_BASE_URL (defaulting to https://dlazy.com/api/ai/tool) while TEAM_BASE_URL is not declared in requires.env or metadata. The script will send the provided TEAM_API_KEY and any base64-encoded local files to that endpoint by default. Requiring a single API key is proportional, but the undeclared base URL and enforced direct execution (bypassing platform wrappers) increase the risk of credential/data exfiltration.
Persistence & Privilege
The skill does not request always:true and does not modify other skills or system configs. It does, however, instruct direct system execution rather than using the platform runner — a behavioral instruction (already noted) but not a persistence/privilege escalation by itself.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install lrshuai-image-to-video - 安装完成后,直接呼叫该 Skill 的名称或使用
/lrshuai-image-to-video触发 - 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
v1.0.2
- Bumped version to 1.0.2.
- Documentation or metadata updates; no user-facing feature changes.
v1.0.1
- Updated supported models list to include new video generation models (Veo 3.1, Sora 2, Kling V3, and more).
- Removed previously listed models that are no longer supported.
- Example usage updated to reflect new model options.
v1.0.0
Initial release of lrshuAI-image-to-video.
- Generates videos from a single image and text description using multiple supported models.
- Supports popular video generation models including Doubao PixelDance, OpenAI Sora, Luma Ray, Kling, Jimeng, and Vidu.
- Direct invocation required using `python script/invoke_model.py`; do not use `openclaw run`.
- Requires `TEAM_API_KEY` environment variable.
元数据
常见问题
LrshuAI Image To Video 是什么?
参考生视频技能。当你需要提供一张图片和文本描述来生成视频时调用此技能。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 101 次。
如何安装 LrshuAI Image To Video?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install lrshuai-image-to-video」即可一键安装,无需额外配置。
LrshuAI Image To Video 是免费的吗?
是的,LrshuAI Image To Video 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
LrshuAI Image To Video 支持哪些平台?
LrshuAI Image To Video 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 LrshuAI Image To Video?
由 dlazyAI(@lrshu)开发并维护,当前版本 v1.0.2。
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