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Free Video Generation From Prompt

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install free-video-generation-from-prompt
功能描述
Skip the learning curve of professional editing software. Describe what you want — generate a 30-second video of a futuristic city at night with ambient musi...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "generate a short text description like 'a sunset over mountains with calm music' into a 1080p MP4"
  • "generate a 30-second video of a futuristic city at night with ambient music"
  • "creating videos from text descriptions without any footage for content creators, marketers, students"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Free Video Generation from Prompt — Create Videos from Text Prompts

Send me your text prompt and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a short text description like 'a sunset over mountains with calm music', type "generate a 30-second video of a futuristic city at night with ambient music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter and more specific prompts tend to produce more accurate and consistent results.

Matching Input to Actions

User prompts referencing free video generation from prompt, 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.

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

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

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute 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)

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=\x3Cid>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Common Workflows

Quick edit: Upload → "generate a 30-second video of a futuristic city at night with ambient 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a 30-second video of a futuristic city at night with ambient music" — concrete instructions get better results.

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

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

安全使用建议
This skill appears to do what it claims: connect to an external nemovideo API, optionally create an anonymous token, upload user-supplied text/files, and return rendered video URLs. Before installing, consider: (1) the API base (https://mega-api-prod.nemovideo.ai) is an external service of unknown reputation — verify the service if you care about data handling; (2) the skill may create or store an anonymous NEMO_TOKEN (100 credits, 7-day expiry) and save session_id locally (it may write to a config directory per the SKILL.md frontmatter); (3) do not upload sensitive files (private keys, passwords, proprietary documents) since uploads go to the service; (4) clarify the metadata mismatch about config paths with the publisher if you want precise guarantees about local config access. If you trust the external service and avoid uploading sensitive material, the skill's behavior is coherent with its stated purpose.
功能分析
Type: OpenClaw Skill Name: free-video-generation-from-prompt Version: 1.0.0 The skill bundle provides instructions for an AI agent to interface with a video generation service at nemovideo.ai. It outlines standard API interactions, including anonymous token acquisition, session management, and file uploads. While it requests access to environment variables (NEMO_TOKEN) and performs platform detection by checking local paths (e.g., ~/.cursor/skills/), these actions are consistent with the stated functionality of a cloud-based media processing tool and do not show evidence of malicious intent or data exfiltration.
能力评估
Purpose & Capability
Name/description (text-to-video) matches requested capability (NEMO_TOKEN, remote render API, upload endpoints). Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) under metadata.openclaw.requires.configPaths, but the registry metadata reported 'Required config paths: none'. Reading a config path or detecting install path is plausible for attribution/session persistence, but the registry-record mismatch should be clarified.
Instruction Scope
Instructions confine actions to creating/using a session with the nemovideo API, sending SSE messages, uploading user-provided files, polling render status, and returning download URLs. The skill does not instruct the agent to read unrelated system files or other environment variables beyond NEMO_TOKEN, though it does ask the agent to inspect its own SKILL.md frontmatter and detect install path for attribution headers (reasonable for provenance but requires filesystem checks).
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. All network interactions are runtime API calls; no archives or third-party packages are downloaded by an installer.
Credentials
Only a single credential (NEMO_TOKEN) is declared as required and is appropriate for a service that needs an API token. Note: SKILL.md describes acquiring an anonymous token via an API call and storing it as NEMO_TOKEN, and frontmatter references a local config path (~/.config/nemovideo/) which could be used for storing tokens/session info — this is plausible but the registry metadata did not declare any config paths, creating a small inconsistency to verify.
Persistence & Privilege
No elevated privileges requested. always:false and normal autonomous invocation. The skill instructs saving session_id (expected for session management) but does not request system-wide config changes or other skills' 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 free-video-generation-from-prompt
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-video-generation-from-prompt 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 Free Video Generation from Prompt skill. - Instantly generate AI videos (up to 30 seconds) from text prompts or documents (TXT, DOCX, PDF, up to 500MB). - Simple onboarding: automatic anonymous token setup and connection to remote GPU-powered video generation. - Supports various formats (mp4, mov, avi, webm, mkv, images, audio). - File upload, progress updates, job status, and credit balance checking included. - Export videos quickly without editing skills, camera, or stock footage. - Designed for content creators, marketers, and students seeking fast video creation from plain text.
元数据
Slug free-video-generation-from-prompt
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 Video Generation From Prompt 是什么?

Skip the learning curve of professional editing software. Describe what you want — generate a 30-second video of a futuristic city at night with ambient musi... 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 Free Video Generation From Prompt?

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

Free Video Generation From Prompt 是免费的吗?

是的,Free Video Generation From Prompt 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Free Video Generation From Prompt 支持哪些平台?

Free Video Generation From Prompt 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 Video Generation From Prompt?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

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