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francemichaell-15

Text To Video Models

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
67
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install text-to-video-models
功能描述
Skip the learning curve of professional editing software. Describe what you want — generate a 10-second clip of a sunset over a city skyline with cinematic c...
安全使用建议
This skill will send your prompts, uploaded files (up to 500MB), and a session token to an external API at mega-api-prod.nemovideo.ai and may create a temporary anonymous token if you don't supply NEMO_TOKEN. Before installing: (1) confirm the skill's source/homepage and privacy/retention policy for uploaded files, (2) avoid uploading sensitive or proprietary files, (3) prefer supplying your own API token if you trust the provider, (4) ask why the skill frontmatter mentions ~/.config/nemovideo/ (the registry metadata did not) — that could indicate it expects local config access, and (5) verify any costs/credits and how tokens are used/expired. If you can't verify the source or data handling, consider not installing or only using dummy/test content.
功能分析
Type: OpenClaw Skill Name: text-to-video-models Version: 1.0.0 The skill bundle provides a legitimate integration for a text-to-video generation service via the nemovideo.ai API. It handles authentication (using NEMO_TOKEN or anonymous tokens), session management, and video rendering workflows as described in SKILL.md. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the requested access to ~/.config/nemovideo/ and environment variables is consistent with the tool's stated purpose.
能力评估
Purpose & Capability
The declared purpose (text-to-video generation) matches the API endpoints and flows described in SKILL.md and the single required credential (NEMO_TOKEN). However the SKILL.md frontmatter lists a required config path (~/.config/nemovideo/) while the registry metadata reported no required config paths — an inconsistency between packaging and runtime instructions that should be clarified.
Instruction Scope
Instructions tell the agent to create or use a bearer token, upload user files (up to 500MB) and send them to https://mega-api-prod.nemovideo.ai, start render jobs, read SSE streams, and poll state. Uploading arbitrary user files and session state to an external service is expected for this kind of skill, but it is sensitive: users' uploads and generated tokens will be sent off-platform. The doc also asks to auto-detect an install path for X-Skill-Platform attribution (vague) and requires specific attribution headers on every request — this is operationally fine but enforces outgoing requests that identify the skill. The instructions do not ask for unrelated local files or secrets, but the file-upload and token-creation behaviors are the primary privacy/risk surface.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only. That minimizes disk/installation risk because nothing will be downloaded or written by an installer.
Credentials
Only one env var (NEMO_TOKEN) is declared as required/primary, which is proportionate for a cloud API client. The SKILL.md also documents a fallback anonymous-token flow (generates a UUID and obtains a temporary token), which means the skill can operate without a user-provided secret. The discrepancy between the registry's 'no config paths' and the frontmatter's configPaths entry (~/.config/nemovideo/) should be resolved — requesting access to a user's config directory would be more sensitive and needs justification.
Persistence & Privilege
always is false and the skill does not request persistent platform-level privileges. Autonomous invocation is allowed (platform default) — combined with outbound network access this increases blast radius but is normal for an API-based generator. The skill does not claim to modify other skills or system-wide settings.
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 text-to-video-models
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /text-to-video-models 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 Text to Video Models — generate AI videos from text prompts. - Upload text files or describe your video idea to generate 10-second AI video clips in about 1–3 minutes. - Supports TXT, DOCX, PDF, and CSV uploads up to 500MB. - Integrated cloud render pipeline with 1080p MP4 output. - Session-based workflow enables iterative editing and batch processing. - Handles credits, exports, file upload, and status via easy chat commands. - Designed for marketers, filmmakers, and content creators seeking simple, camera-free video generation.
元数据
Slug text-to-video-models
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

Text To Video Models 是什么?

Skip the learning curve of professional editing software. Describe what you want — generate a 10-second clip of a sunset over a city skyline with cinematic c... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 67 次。

如何安装 Text To Video Models?

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

Text To Video Models 是免费的吗?

是的,Text To Video Models 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Text To Video Models 支持哪些平台?

Text To Video Models 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 Text To Video Models?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

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