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Image To Video Kaise Banaye

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install image-to-video-kaise-banaye
功能描述
Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting still images into shareable vid...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "convert three product photos in JPG format into a 1080p MP4"
  • "image se video banao background music ke saath"
  • "converting still images into shareable videos for Instagram and YouTube creators"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Image to Video Kaise Banaye — Convert Images into MP4 Videos

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

Here's a typical use: you send a three product photos in JPG format, ask for image se video banao background music ke saath, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — use high-resolution images for sharper output video quality.

Matching Input to Actions

User prompts referencing image to video kaise banaye, 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-kaise-banaye, 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).

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 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)

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.

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 → "image se video banao background music ke saath" → 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 "image se video banao background music ke saath" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across all platforms.

安全使用建议
This skill appears to do what it says — it uploads your images to an external service (mega-api-prod.nemovideo.ai) and returns rendered MP4s. Before installing or using it: (1) Verify the provider (there's no homepage or publisher info); (2) Do not upload sensitive images — uploads go to an external, unverified host; (3) Only provide a NEMO_TOKEN that is scoped/dedicated to this service (do not reuse long-lived tokens you use elsewhere); (4) Ask the author to clarify the config path discrepancy (~/.config/nemovideo/ vs. 'none' in registry metadata) and for a privacy/retention policy for uploaded media; (5) If you want to test, try non-sensitive images first and confirm where downloads are hosted and how long files are retained. These steps will reduce privacy and trust risks.
能力评估
Purpose & Capability
Name/description match the instructions: the skill uploads images and calls an external video-rendering API. Requesting a single NEMO_TOKEN credential is consistent with a third‑party media API. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported 'required config paths: none' — that's an internal inconsistency worth clarifying.
Instruction Scope
The instructions tell the agent to upload user-supplied images and poll/stream results from https://mega-api-prod.nemovideo.ai and to include Authorization: Bearer <NEMO_TOKEN>. That is expected for a cloud render service but means user images and any supplied token will be transmitted to an external, unknown backend. The skill also instructs acquiring an anonymous token if no NEMO_TOKEN is present, which requires generating a UUID and POSTing to the same unknown endpoint. No instructions ask the agent to read unrelated files or other env vars, but the explicit upload of potentially sensitive images to an unverified third party is a privacy risk.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest disk/write risk. There is no package download or archive extraction.
Credentials
Only one environment variable is required (NEMO_TOKEN), which is proportionate for a service that authenticates API calls. Caveats: the SKILL.md frontmatter implies a config path (~/.config/nemovideo/) and the registry metadata did not list it — inconsistent. The skill will use any NEMO_TOKEN found in the environment; ensure that token is dedicated to this service and not reused for other services to avoid accidental exfiltration.
Persistence & Privilege
always:false (normal). The skill is user-invocable and can be invoked autonomously (default), which is expected. It does not request to modify other skills or system-wide settings. Note: autonomous invocation combined with networked upload capability increases blast radius if the skill were malicious — consider this in your risk decision.
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-kaise-banaye
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-kaise-banaye 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
Image to Video Kaise Banaye — Initial Release - Instantly converts up to three JPG product images into 1080p MP4 video clips with simple text instructions. - No timeline editing or export settings required; just upload, describe, and download within 30–60 seconds. - Supports background music, text overlays, aspect ratio adjustments, and quick exports for social sharing. - Automatic handling of sessions and authentication with 100 free credits for new users. - Batch processing and iterative editing supported via session state. - User-friendly error messages and format support for MP4, MOV, AVI, WEBM, MKV, JPG, PNG, GIF, WEBP, MP3, WAV, M4A, AAC.
元数据
Slug image-to-video-kaise-banaye
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 Kaise Banaye 是什么?

Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting still images into shareable vid... 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 Kaise Banaye?

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

Image To Video Kaise Banaye 是免费的吗?

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

Image To Video Kaise Banaye 支持哪些平台?

Image To Video Kaise Banaye 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 Kaise Banaye?

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

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