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Ai Image To Video Generate

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-image-to-video-generate
功能描述
generate still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 50MB. marketers, social media creators, designer...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "generate my still images"
  • "export 1080p MP4"
  • "turn this image into a 10-second"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

AI Image to Video Generate — Convert Images Into Video Clips

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

Say you have a single product photo or illustration and want to turn this image into a 10-second animated video clip — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: high-contrast images with clear subjects produce smoother motion results.

Matching Input to Actions

User prompts referencing ai image to video generate, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

Formats: 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: ai-image-to-video-generate
  • 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.

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)

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.

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 this image into a 10-second animated video clip" — concrete instructions get better results.

Max file size is 50MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

PNG images with clean backgrounds give the AI more accurate subject detection.

Common Workflows

Quick edit: Upload → "turn this image into a 10-second animated video clip" → Download MP4. Takes 30-60 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 do what it says: it connects to the Nemovideo cloud API, uploads images, and returns rendered video files. Before installing, consider: (1) You will be sending images to https://mega-api-prod.nemovideo.ai — do not upload private or sensitive images you wouldn't want processed by a third party. (2) The skill uses (or will obtain) an API token (NEMO_TOKEN); if you provide your own token, ensure it is scoped appropriately and not a high-privilege secret used elsewhere. (3) SKILL.md mentions reading the skill file and detecting install paths to populate attribution headers and also lists a config path (~/.config/nemovideo/) in its frontmatter — this metadata mismatch is minor but means the skill may look for that config directory. (4) No installers or external downloads are performed by the skill (instruction-only), which reduces disk-write risk. If you need stronger assurance: verify the domain and service (nemovideo.ai) independently, and avoid supplying any tokens that grant broad unrelated privileges.
功能分析
Type: OpenClaw Skill Name: ai-image-to-video-generate Version: 1.0.0 The skill is a legitimate integration for an AI image-to-video generation service (nemovideo.ai). It provides instructions for the agent to manage sessions, upload media, and poll for render results via a cloud API. It includes security-conscious instructions to avoid exposing tokens and uses standard API patterns for its stated purpose without evidence of malicious intent or data exfiltration.
能力评估
Purpose & Capability
The skill's name/description match the instructions: it uploads images, creates a session, streams edits, and requests exports from a cloud rendering backend. The single required environment variable (NEMO_TOKEN) is appropriate for an API-backed service. Minor inconsistency: the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths.
Instruction Scope
SKILL.md stays focused on connecting to the Nemovideo API, uploading files, handling SSE streams, polling exports, and mapping GUI actions to API calls. It instructs the agent to read the skill's YAML frontmatter and detect install path (~/.clawhub, ~/.cursor/skills/) to populate X-Skill-Platform—this requires reading the skill file and inspecting install paths but is limited in scope and consistent with adding attribution headers. It does not instruct the agent to read unrelated system files or other credentials.
Install Mechanism
No install spec or code files — instruction-only. Nothing is downloaded or written to disk by an install step, which minimizes risk.
Credentials
Only NEMO_TOKEN is required and is the logical primary credential for a cloud rendering API. The SKILL.md also describes generating an anonymous token by POSTing to the service when no NEMO_TOKEN is present (ephemeral token, 100 free credits, 7-day expiry), which is reasonable but means the agent will obtain and use an API token at runtime. The presence of a configPaths entry in the SKILL.md metadata (not reflected in registry metadata) is an unexplained discrepancy — it implies possible read access to ~/.config/nemovideo/, which is not declared elsewhere.
Persistence & Privilege
always:false and normal autonomous invocation are used. The skill stores transient session_id and tokens for API interactions (expected). It does not request persistent or cross-skill modifications or elevated system privileges.
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-generate
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-image-to-video-generate 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 AI Image to Video Generate skill. - Convert still images (JPG, PNG, WEBP, HEIC up to 50MB) into animated 1080p MP4 video clips using a cloud backend. - Automatic user setup with token acquisition and session management. - Supports uploads, timeline editing, credits checking, and video export via intuitive prompts. - Provides rapid cloud rendering (30-60 seconds per video) with real-time session updates. - Full error handling for uploads, exports, session, and credit issues. - Designed for marketers, creators, and designers converting static images to engaging video content.
元数据
Slug ai-image-to-video-generate
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 Generate 是什么?

generate still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 50MB. marketers, social media creators, designer... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 94 次。

如何安装 Ai Image To Video Generate?

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

Ai Image To Video Generate 是免费的吗?

是的,Ai Image To Video Generate 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 Generate 支持哪些平台?

Ai Image To Video Generate 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 Generate?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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