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tk8544-b

Diffusion Video

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install diffusion-video
功能描述
Turn a still landscape photo or short reference clip into 1080p diffusion-generated video clips just by typing what you need. Whether it's generating AI anim...
使用说明 (SKILL.md)

Getting Started

Got images or video to work with? Send it over and tell me what you need — I'll take care of the AI diffusion video generation.

Try saying:

  • "generate a still landscape photo or short reference clip into a 1080p MP4"
  • "animate this image into a 5-second diffusion video with cinematic motion"
  • "generating AI animated videos from still images or text prompts for content creators, AI artists, marketers"

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.

Diffusion Video — Generate AI Diffusion Video Clips

Send me your images or video and describe the result you want. The AI diffusion video generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a still landscape photo or short reference clip, type "animate this image into a 5-second diffusion video with cinematic motion", and you'll get a 1080p MP4 back in roughly 1-3 minutes. All rendering happens server-side.

Worth noting: simpler, high-contrast images produce cleaner diffusion motion results.

Matching Input to Actions

User prompts referencing diffusion video, 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.

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

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

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.

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

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

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.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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 "animate this image into a 5-second diffusion video with cinematic motion" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for widest platform compatibility.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second diffusion video with cinematic motion" → Download MP4. Takes 1-3 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 sends any images/videos you provide to the external service at mega-api-prod.nemovideo.ai and uses a NEMO_TOKEN (or obtains an anonymous token) to process and return rendered videos. Before installing or using: (1) Verify you trust the nemo service and its privacy/retention policy because uploaded media will leave your machine; (2) Prefer using a personal account token over anonymous tokens if you need auditability/control; (3) Ask the skill author to clarify the config-path behavior (the SKILL.md references ~/.config/nemovideo/ and auto-detecting install path) because that implies local file access not otherwise documented in registry metadata; (4) Don't provide other secrets or sensitive files to the skill. If you want stronger assurances, request the skill to document exactly what it reads/writes locally and to remove or explain the configPath/install-path auto-detection.
功能分析
Type: OpenClaw Skill Name: diffusion-video Version: 1.0.0 The diffusion-video skill is a legitimate integration for an AI video generation service hosted at nemovideo.ai. It provides clear instructions for the agent to manage authentication tokens, sessions, and file uploads via standard REST and SSE APIs. The skill's behavior is consistent with its stated purpose of generating and editing video clips, and no indicators of malicious intent, data exfiltration, or unauthorized execution were identified in the SKILL.md or metadata.
能力评估
Purpose & Capability
Name/description describe remote video generation and the skill only requires a single service token (NEMO_TOKEN) and API calls to a video-rendering backend. Asking for an API token and session management is proportionate to the stated purpose.
Instruction Scope
SKILL.md contains concrete API calls for authentication, session creation, SSE streaming, uploads, and export polling — all consistent with a remote render service. Minor scope notes: the frontmatter mentions a config path (~/.config/nemovideo/) and the doc asks to auto-detect install-path for X-Skill-Platform — these imply the agent may read runtime/install path or local config, which is not strictly necessary for basic operation and is inconsistent with the registry metadata that listed no config paths.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing is downloaded or written to disk by an install step. Low installation risk.
Credentials
Only a single service credential (NEMO_TOKEN) is required and used in the documented API flows. The SKILL.md explicitly supports generating an anonymous token if no env var is set. No unrelated secrets or broad system credentials are requested.
Persistence & Privilege
Skill is not always-enabled and uses normal autonomous invocation. It instructs saving session_id for the rendering session (expected). The earlier-mentioned config path in frontmatter suggests it may read or write under ~/.config/nemovideo/ — that capability is not declared in the registry metadata and should be clarified if true.
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 diffusion-video
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /diffusion-video 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 Diffusion Video — Generate AI Diffusion Video Clips. - Generate 1080p AI diffusion video clips from still images or reference videos via simple typed instructions. - Seamless onboarding: automatic token/session management; no setup required. - Handles uploads, timeline edits, exports, credits, and state queries via cloud GPU processing. - Fast rendering pipeline: 1–3 minutes per video, returns downloadable MP4. - Built-in error handling for tokens, sessions, credits, rate limits, and file issues. - Supports multiple formats (MP4, MOV, PNG, JPG, GIF, audio); max file size 200MB.
元数据
Slug diffusion-video
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

Diffusion Video 是什么?

Turn a still landscape photo or short reference clip into 1080p diffusion-generated video clips just by typing what you need. Whether it's generating AI anim... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 100 次。

如何安装 Diffusion Video?

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

Diffusion Video 是免费的吗?

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

Diffusion Video 支持哪些平台?

Diffusion Video 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 Diffusion Video?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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