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Video Test Udnerc
作者
peandrover adam
· GitHub ↗
· v1.0.0
· MIT-0
97
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install video-test-udnerc
功能描述
Get processed test video ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something lik...
安全使用建议
This skill appears to truly be a cloud video test-render helper, but it will upload any video you give it to https://mega-api-prod.nemovideo.ai and will generate or use a NEMO_TOKEN for authorization. Before using/installing: (1) Be aware that your videos and a session token may be sent to and stored by an external service. (2) The SKILL.md references writing/reading ~/.config/nemovideo/ but the registry didn't declare that — ask the publisher where session/tokens are stored and whether they are kept on disk. (3) If you want more control, set your own NEMO_TOKEN rather than letting the skill auto-create one, and avoid uploading sensitive content until you verify the service/privacy policy. (4) Because the skill's source/homepage is unknown, prefer caution: confirm the service domain and privacy/security practices or only use test/non-sensitive footage.
功能分析
Type: OpenClaw Skill
Name: video-test-udnerc
Version: 1.0.0
The skill 'video-test-udnerc' is a legitimate integration for a cloud-based video rendering service (nemovideo.ai). It provides detailed instructions for the AI agent to manage authentication via a NEMO_TOKEN, handle sessions, and interface with specific API endpoints for video processing, status checks, and exports. While it includes instructions for the agent to perform minor environment discovery (checking install paths for attribution headers) and to automatically connect to the backend, these actions are aligned with the stated purpose of providing a seamless video editing experience and do not exhibit signs of data exfiltration, malicious execution, or unauthorized access.
能力评估
Purpose & Capability
Name/description, endpoints and actions all align with a cloud video-processing skill. Requesting a NEMO_TOKEN credential is expected. However, the SKILL.md metadata references a config path (~/.config/nemovideo/) for storage even though the skill registry metadata listed no required config paths — that's an internal inconsistency and suggests the skill intends to persist state on disk.
Instruction Scope
Instructions remain within video-processing scope (create session, upload video, poll export, read SSE). They explicitly instruct generating an anonymous token if NEMO_TOKEN is absent and storing session_id for subsequent calls. This means the agent will contact an external domain and upload user-provided video files; that is expected for this service but is notable: user content and tokens will be sent off-host. The doc also instructs the agent not to display raw API responses or tokens to users, which limits visibility into what is being stored/transmitted.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. Nothing is downloaded or written by an installer step described in the registry.
Credentials
The only declared environment credential is NEMO_TOKEN (primaryEnv), which is reasonable. However, SKILL.md metadata includes a config path (~/.config/nemovideo/) and the instructions instruct generating and storing anonymous tokens/session IDs if NEMO_TOKEN is missing. The registry did not declare config path requirements earlier — mismatch. Persisting tokens/session state to disk without declaring it is disproportionate to what was advertised and reduces transparency.
Persistence & Privilege
always:false and no autonomous-invocation override — ordinary. But the skill's instructions explicitly create and persist anonymous tokens and session IDs and reference a user config directory; this implies on-disk persistence of credentials and job state. That persistence is not announced in the registry metadata and could be surprising to users.
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 video-test-udnerc - 安装完成后，直接呼叫该 Skill 的名称或使用
/video-test-udnerc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
v1.0.0
Initial release of Video Test Render — Test and Export Video Files
- Upload raw video and request test renders to quickly verify quality and playback settings.
- Automatic connection and authentication with cloud video processing backend; 100 free credits issued to new users.
- Handles common video formats (MP4, MOV, AVI, WebM; max 500MB) and outputs 1080p MP4 files.
- Easy command workflows for exporting videos, checking credits, viewing status, and batch or iterative editing.
- Clear guidance on supported actions, error codes, and troubleshooting.
元数据
常见问题
Video Test Udnerc 是什么？
Get processed test video ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something lik... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 97 次。
如何安装 Video Test Udnerc？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install video-test-udnerc」即可一键安装，无需额外配置。
Video Test Udnerc 是免费的吗？
是的，Video Test Udnerc 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Video Test Udnerc 支持哪些平台？
Video Test Udnerc 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 Video Test Udnerc？
由 peandrover adam（@peand-rover）开发并维护，当前版本 v1.0.0。
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