← 返回 Skills 市场
whitejohnk-26

Ai Image To Video Ltx

作者 whitejohnk-26 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
65
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install ai-image-to-video-ltx
功能描述
Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, BMP, up to 20MB), say something like "ani...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "animate this image into a 5-second"

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.

AI Image to Video LTX — Animate Images into Video Clips

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

Here's a typical use: you send a a single product photo or illustrated scene, ask for animate this image into a 5-second video clip using LTX, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — clean, high-contrast images with a clear subject produce the smoothest motion results.

Matching Input to Actions

User prompts referencing ai image to video ltx, 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 ai-image-to-video-ltx
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 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

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

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 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 "animate this image into a 5-second video clip using LTX" — concrete instructions get better results.

Max file size is 20MB. Stick to JPG, PNG, WEBP, BMP for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video clip using LTX" → Download MP4. Takes 30-90 seconds 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 call a third-party API to turn uploaded images into videos and will upload your files to mega-api-prod.nemovideo.ai. The provider and homepage are unknown — verify the service's reputation and privacy policy before sending sensitive images. Clarify how and where the anonymous token (NEMO_TOKEN) and session_id are stored (environment variable vs config file under ~/.config/nemovideo/), and whether tokens persist beyond 7 days. If you don't want files or tokens stored or sent to an unknown service, do not install; otherwise proceed with caution and consider using throwaway accounts or anonymized images. If possible, ask the publisher for a homepage/source repository and details on data retention and token storage to increase confidence.
功能分析
Type: OpenClaw Skill Name: ai-image-to-video-ltx Version: 1.0.0 The skill is a functional wrapper for an AI image-to-video generation service hosted at `mega-api-prod.nemovideo.ai`. It defines standard API interactions for authentication, session management, and file uploads, including a fallback mechanism to acquire anonymous tokens. The instructions in `SKILL.md` are aligned with the stated purpose and include security best practices, such as advising the agent not to display raw tokens or API responses to the user.
能力评估
Purpose & Capability
The name/description (animate still images into video) aligns with the API endpoints and flows described in SKILL.md (upload, render, export). Requiring a NEMO_TOKEN is expected for a hosted rendering service. However, the skill metadata declares a required config path (~/.config/nemovideo/) that the runtime instructions never reference explicitly, which is an unexplained mismatch.
Instruction Scope
The SKILL.md stays mostly within the stated purpose: it instructs the agent to obtain/refresh an anonymous token, create a session, upload user-supplied images, kick off renders, poll for completion, and return download URLs. It does instruct automatic anonymous token provisioning and to 'store' the session_id (and implies the token is NEMO_TOKEN) but is vague about where/how the token/session are persisted. The skill will upload user files to a third-party domain (mega-api-prod.nemovideo.ai) — expected for functionality but a privacy consideration. It also instructs suppressing display of raw API responses/tokens, which reduces transparency.
Install Mechanism
No install steps or code files are present (instruction-only), so nothing is written to disk or downloaded by an install script. This lowers technical risk, but the runtime will make network calls to the provider's API.
Credentials
Only one credential is requested (NEMO_TOKEN), which is proportional to a cloud-rendering service. However, metadata also lists a config path (~/.config/nemovideo/) without SKILL.md instructions for reading/writing it; this inconsistency should be clarified. The skill's automatic anonymous-token acquisition flow means the agent may create/store tokens on behalf of the user if no token is present.
Persistence & Privilege
The skill does not request 'always: true' and has no install-time persistence instructions in SKILL.md beyond storing a session_id/token for use with subsequent requests. There is no instruction 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 ai-image-to-video-ltx
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-image-to-video-ltx 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
AI Image to Video LTX skill — initial release. - Instantly animates still images into 1080p MP4 video clips using cloud AI, no manual editing required. - Supports upload of JPG, PNG, WEBP, BMP images (up to 20MB) and batch processing. - Seamless authentication and session handling with automatic free token generation for new users. - Exports ready-to-share video clips in 30–90 seconds; workflow designed for content creators and social media managers. - Built-in commands for upload, editing, preview, balance checking, and export—all accessible via natural language prompts. - Robust error handling, session recovery, and clear user communication throughout the process.
元数据
Slug ai-image-to-video-ltx
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

Ai Image To Video Ltx 是什么?

Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, BMP, up to 20MB), say something like "ani... 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 Ai Image To Video Ltx?

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

Ai Image To Video Ltx 是免费的吗?

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

Ai Image To Video Ltx 支持哪些平台?

Ai Image To Video Ltx 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 Ai Image To Video Ltx?

由 whitejohnk-26(@whitejohnk-26)开发并维护,当前版本 v1.0.0。

💬 留言讨论