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francemichaell-15

Image To Video No Ai

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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在 OpenClaw 中安装
/install image-to-video-no-ai
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn these photos into a slideshow video with transitions and music — and...
使用说明 (SKILL.md)

Getting Started

Send me your still images and I'll handle the manual video creation. Or just describe what you're after.

Try saying:

  • "convert five product photos in JPG format into a 1080p MP4"
  • "turn these photos into a slideshow video with transitions and music"
  • "converting photo sets into videos without AI generation for marketers, social media creators"

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.

Image to Video No AI — Convert Photos into Videos

Send me your still images and describe the result you want. The manual video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload five product photos in JPG format, type "turn these photos into a slideshow video with transitions and music", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer images with longer durations per slide produces smoother results.

Matching Input to Actions

User prompts referencing image to video no ai, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-no-ai, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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

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)

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

Common Workflows

Quick edit: Upload → "turn these photos into a slideshow video with transitions and music" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a slideshow video with transitions and music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.

安全使用建议
This skill will upload any images you send to the external domain https://mega-api-prod.nemovideo.ai and use an API token (NEMO_TOKEN) to create/session and render videos. If you don't provide a token, the skill will call the service's anonymous-token endpoint to obtain one and store the returned token/session for subsequent requests. Before installing or using it, consider: (1) Are you comfortable with your images being sent to that third-party service? (2) Verify the service/domain is legitimate and read its privacy/retention policy for uploaded media. (3) If you prefer not to persist a long-lived token, supply an ephemeral token or clear stored credentials after use. (4) Note the small metadata mismatch (config path listed in the skill YAML but not in registry) — this appears to be a bookkeeping inconsistency, not a functional red flag. If you need absolute offline guarantees, do not install or use this skill because its whole function is remote rendering.
功能分析
Type: OpenClaw Skill Name: image-to-video-no-ai Version: 1.0.0 The skill 'image-to-video-no-ai' is a functional integration for a cloud-based video rendering service (nemovideo.ai). It provides instructions for the agent to manage authentication, sessions, and file uploads to 'mega-api-prod.nemovideo.ai'. While it includes logic for automated token acquisition and platform detection via installation paths, these behaviors are consistent with the skill's stated purpose and do not exhibit signs of malicious intent or unauthorized data exfiltration.
能力评估
Purpose & Capability
The skill is an instruction-only adapter for a remote image→video rendering service. Requesting NEMO_TOKEN (the API token) fits the described behavior. Minor inconsistency: the SKILL.md frontmatter names a config path (~/.config/nemovideo/) while the registry metadata reports no required config paths — this is likely a bookkeeping mismatch but does not change capability alignment.
Instruction Scope
The instructions stay within the stated purpose: obtain/validate a token, create a session, upload images, drive edits via SSE, poll for export and return download URLs. They do instruct generating an anonymous token automatically if NEMO_TOKEN is not present and storing session_id/token for subsequent calls. The doc also mentions deriving an attribution header from the agent's install path (checking ~/.clawhub/ or ~/.cursor/skills/), which implies the agent may inspect its runtime/install path; this is a small scope expansion but understandable for attribution. No instructions read unrelated system files or request unrelated credentials.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only, so nothing is written to disk by an installer. This is the lowest-risk install model.
Credentials
Only one environment credential is declared (NEMO_TOKEN) and is necessary to authenticate to the described API. The skill can generate an anonymous token if none is present; no other secrets or unrelated env vars are requested.
Persistence & Privilege
The skill is not marked always:true and does not request elevated privileges or modify other skills. It asks to store a session_id/token for use during the session, which is expected for a remote service client. Autonomous invocation is allowed but that is the platform default and not in itself unusual here.
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 image-to-video-no-ai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-no-ai 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 Image to Video No AI — quickly convert your photos into slideshow videos, no AI-generated content required. - Upload JPG, PNG, WEBP, or GIF files up to 200MB and receive a rendered MP4 video in 30-60 seconds - Handles authentication, session creation, and remote GPU-based rendering automatically - Supports video customization: transitions, music, 1080p output, aspect ratio, text overlays, and audio tracks - Simple workflows for quick edits, batch processing, and iterative refinement - Users receive clear, concise feedback during video creation and export - Displays helpful error messages for authentication, upload, or rendering issues
元数据
Slug image-to-video-no-ai
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

Image To Video No Ai 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn these photos into a slideshow video with transitions and music — and... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 74 次。

如何安装 Image To Video No Ai?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install image-to-video-no-ai」即可一键安装,无需额外配置。

Image To Video No Ai 是免费的吗?

是的,Image To Video No Ai 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Image To Video No Ai 支持哪些平台?

Image To Video No Ai 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 Image To Video No Ai?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

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