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Video Leonardo Easy

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
30
总下载
0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install video-leonardo-easy
功能描述
Get AI generated videos ready to post, without touching a single slider. Upload your images or prompts (MP4, MOV, PNG, JPG, up to 200MB), say something like...
使用说明 (SKILL.md)

Getting Started

Share your images or prompts and I'll get started on AI video generation. Or just tell me what you're thinking.

Try saying:

  • "generate my images or prompts"
  • "export 1080p MP4"
  • "turn these product photos into a"

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.

Video Leonardo Easy — Generate Videos from Images

This tool takes your images or prompts and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have three product images and a text prompt and want to turn these product photos into a short promotional video clip — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: simpler prompts with clear subjects tend to produce more consistent motion.

Matching Input to Actions

User prompts referencing video leonardo easy, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source video-leonardo-easy
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these product photos into a short promotional video clip" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, PNG, JPG for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "turn these product photos into a short promotional video clip" → 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 purpose-aligned for cloud AI video generation. Before installing, understand that it may automatically create a NemoVideo session, use or create a NEMO_TOKEN, and upload your selected files and prompts to the NemoVideo backend. Avoid using it with confidential media unless you trust that provider's privacy and retention practices.
功能分析
Type: OpenClaw Skill Name: video-leonardo-easy Version: 1.0.0 The video-leonardo-easy skill is a standard integration for an AI video generation service hosted at mega-api-prod.nemovideo.ai. The SKILL.md file provides clear instructions for the agent to handle authentication via the NEMO_TOKEN environment variable, manage user sessions, and interface with the cloud rendering pipeline. While it includes capabilities for file uploads and automated API interactions, these are strictly aligned with the stated purpose of generating and exporting videos, and there is no evidence of data exfiltration, unauthorized access, or malicious intent.
能力评估
Purpose & Capability
The skill's stated purpose and capabilities align: it generates and exports videos from user images or prompts through a cloud rendering API. The noteworthy part is that user content is processed by an external service.
Instruction Scope
Instructions include automatic first-time backend connection and translating backend GUI-style responses into follow-up API actions. This appears limited to the video workflow, but users should understand the automation.
Install Mechanism
No install spec, binaries, or code files are present; this is an instruction-only skill. The required NEMO_TOKEN is disclosed in the supplied requirements and SKILL metadata.
Credentials
External network calls to mega-api-prod.nemovideo.ai and media uploads are proportionate to cloud video generation, but users should avoid uploading confidential content unless they trust the service.
Persistence & Privilege
The skill uses a bearer token or auto-created anonymous token and stores a session_id for subsequent requests. No elevated local privileges, background persistence, or broad local file access are shown.
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 video-leonardo-easy
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-leonardo-easy 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 Video Leonardo Easy: generate videos from images or prompts with a simple, fast workflow. - Supports uploads of MP4, MOV, PNG, JPG (up to 200MB) and basic prompt-based generation. - Automatic setup with free token for new users; 100 free credits valid for 7 days. - Download generated videos in 1080p MP4; compatible with multiple formats. - Streamlined cloud rendering pipeline with session and job tracking. - Clear error handling and guidance for uploads, exports, and credit management.
元数据
Slug video-leonardo-easy
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

Video Leonardo Easy 是什么?

Get AI generated videos ready to post, without touching a single slider. Upload your images or prompts (MP4, MOV, PNG, JPG, up to 200MB), say something like... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 30 次。

如何安装 Video Leonardo Easy?

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

Video Leonardo Easy 是免费的吗?

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

Video Leonardo Easy 支持哪些平台?

Video Leonardo Easy 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 Leonardo Easy?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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