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vcarolxhberger

Free Text To Video App

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
65
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当前安装
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在 OpenClaw 中安装
/install free-text-to-video-app
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn this blog intro into a 30-second video with visuals and music — and g...
使用说明 (SKILL.md)

Getting Started

Got text prompts to work with? Send it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

  • "convert a 100-word product description into a 1080p MP4"
  • "turn this blog intro into a 30-second video with visuals and music"
  • "converting written content into shareable videos for content creators, marketers, students"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Free Text to Video App — Convert Text into Shareable Videos

Drop your text prompts in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 100-word product description, ask for turn this blog intro into a 30-second video with visuals and music, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter, focused text produces more accurate and coherent video output.

Matching Input to Actions

User prompts referencing free text to video app, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip SSE?
"export" / "导出" / "download" / "send me the video" → §3.5 Export
"credits" / "积分" / "balance" / "余额" → §3.3 Credits
"status" / "状态" / "show tracks" → §3.4 State
"upload" / "上传" / user sends file → §3.2 Upload
Everything else (generate, edit, add BGM…) → §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: free-text-to-video-app
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Error Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the export workflow

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this blog intro into a 30-second video with visuals and music" — concrete instructions get better results.

Max file size is 500MB. Stick to TXT, DOCX, PDF, copied text for the smoothest experience.

Export as MP4 for widest compatibility across social and web platforms.

Common Workflows

Quick edit: Upload → "turn this blog intro into a 30-second video with visuals and music" → Download MP4. Takes 1-2 minutes for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

安全使用建议
This skill appears to be an instruction-only connector to a third-party video rendering API (mega-api-prod.nemovideo.ai). Before installing: 1) Remember uploads (text/files) go to that external service — do not upload sensitive data or private keys. 2) The skill will use or mint a NEMO_TOKEN and keep session IDs; confirm how your agent stores those tokens (in memory only vs written to disk). 3) The SKILL.md probes your home directories to detect install path and references a local config path (~/.config/nemovideo/) — if you prefer no filesystem checks, avoid installing. 4) The skill metadata in the registry and the SKILL.md have small inconsistencies (declared required env/config vs behavior), and the skill source/homepage are unknown — verify the service's privacy/terms and the publisher before proceeding. 5) Because this is network-only (no local code), the main risk is data sent to the remote API — treat it like granting a web service access to files you upload.
功能分析
Type: OpenClaw Skill Name: free-text-to-video-app Version: 1.0.0 The skill is a functional integration for the NemoVideo AI service, enabling text-to-video generation via the `nemovideo.ai` API. It automates session management, anonymous token acquisition, and file uploads as described in its documentation. While it performs minor environment fingerprinting to determine the host platform (checking for directories like `~/.clawhub/` or `~/.cursor/skills/`), this is explicitly documented as a requirement for API attribution headers and does not appear to be used for malicious purposes.
能力评估
Purpose & Capability
The name/description (convert text into videos) matches the actions described (upload text/files, call a remote rendering API, start exports). Requesting a NEMO_TOKEN to call mega-api-prod.nemovideo.ai is coherent with the stated purpose.
Instruction Scope
Runtime instructions direct the agent to obtain or use NEMO_TOKEN, create sessions, upload user files, stream SSEs, and poll render status — all in-scope. The skill also instructs reading the skill's YAML frontmatter and probing common install paths (~/.clawhub, ~/.cursor/skills/) to populate X-Skill-Platform; this filesystem probing is not strictly necessary for video creation and should be highlighted to the user.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes on-disk write risk; all behavior occurs through runtime instructions and network calls.
Credentials
Registry metadata lists NEMO_TOKEN as required, but SKILL.md describes auto-generating an anonymous token if one is not present — a mismatch. SKILL.md frontmatter also references a config path (~/.config/nemovideo/) that is not declared in the provided requirements. The skill will create/use short-lived tokens and store session_id values; this requires care because secrets/tokens may be written or cached by the agent unless storage behavior is clear.
Persistence & Privilege
always is false and autonomous invocation is allowed (normal). The skill instructs creating and storing session tokens and polling long-running jobs; that persistent session state is expected for rendering but increases the blast radius if tokens are mishandled. No attempt to modify other skills' configs is present.
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 free-text-to-video-app
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-text-to-video-app 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 the Free Text to Video App. - Instantly converts text (TXT, DOCX, PDF, or pasted) into AI-generated videos with visuals and music. - Supports file uploads up to 500MB; handles all editing and export on cloud GPUs. - Includes automatic setup and authentication for first-time users. - Provides clear workflows for uploading, editing, exporting, and checking credit balance. - Built-in error handling guides users through common issues (token expiry, credits, file limits).
元数据
Slug free-text-to-video-app
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

Free Text To Video App 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn this blog intro into a 30-second video with visuals and music — and g... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 Free Text To Video App?

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

Free Text To Video App 是免费的吗?

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

Free Text To Video App 支持哪些平台?

Free Text To Video App 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 Free Text To Video App?

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

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