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Image To Video In Flow

作者 linmillsd7 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install image-to-video-in-flow
功能描述
Turn a single product photo or illustration into 1080p animated video clip just by typing what you need. Whether it's converting static images into video cli...
使用说明 (SKILL.md)

Getting Started

Got still 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 a single product photo or illustration into a 1080p MP4"
  • "turn this image into a 5-second animated video clip inside my flow"
  • "converting static images into video clips within a workflow for content creators, marketers"

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 in Flow — 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 5-second animated video clip inside my flow — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.

Tip: higher contrast images produce cleaner motion results.

Matching Input to Actions

User prompts referencing image to video in flow, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: 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-in-flow, 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.

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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

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 "turn this image into a 5-second animated video clip inside my flow" — concrete instructions get better results.

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

Use PNG for source images to preserve quality before conversion.

Common Workflows

Quick edit: Upload → "turn this image into a 5-second animated video clip inside my flow" → Download MP4. Takes 20-40 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 looks purpose-aligned for cloud video generation. Before using it, be comfortable sending the selected media and prompts to NemoVideo, protect the NEMO_TOKEN, and confirm any export or credit-consuming action.
功能分析
Type: OpenClaw Skill Name: image-to-video-in-flow Version: 1.0.0 The skill is a legitimate integration for an image-to-video conversion service hosted at nemovideo.ai. It provides detailed instructions for the agent to manage API sessions, handle file uploads, and poll for rendering status. No evidence of data exfiltration, malicious command execution, or harmful prompt injection was found; the requested environment variables and configuration paths are consistent with the stated purpose of the tool.
能力评估
Purpose & Capability
Coherent with the stated purpose. Evidence: SKILL.md says, "runs AI video creation through a cloud rendering pipeline" and "You upload, describe what you want, and download the result," so users should understand media is processed off-device.
Instruction Scope
The workflow lets the backend stream drive internal API actions. Evidence: SKILL.md says, "Tool calls stay internal" and maps backend "click [button]" messages to "Execute via API." This appears purpose-aligned but should stay limited to the active editing/render session.
Install Mechanism
No install spec and no code files are present; the static scanner reported no findings, so there is no artifact-backed local executable install behavior to flag.
Credentials
The required NEMO_TOKEN and NemoVideo API calls are proportional to cloud rendering. Evidence: SKILL.md says to use NEMO_TOKEN or acquire an anonymous token, then create a session and call NemoVideo endpoints.
Persistence & Privilege
No background worker, self-start behavior, local writes, privilege escalation, or ongoing local persistence is shown in the provided artifacts; the visible state is a remote session/render job used for the requested workflow.
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-in-flow
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-in-flow 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 — convert static images into video clips via cloud AI workflow: - Upload a still image and describe your desired animation; get a 1080p MP4 video in about 20–40 seconds. - Simple, guided connection: uses environment token or fetches a free starter token automatically. - Handles user requests for upload, export, credit check, and video state. - Supports batch processing, iterative edits, and quick clip generation for content creators. - All requests require proper attribution headers; file support includes common image, video, and audio formats. - Clear user feedback for progress, errors, and when backend actions are needed.
元数据
Slug image-to-video-in-flow
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 In Flow 是什么?

Turn a single product photo or illustration into 1080p animated video clip just by typing what you need. Whether it's converting static images into video cli... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 30 次。

如何安装 Image To Video In Flow?

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

Image To Video In Flow 是免费的吗?

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

Image To Video In Flow 支持哪些平台?

Image To Video In Flow 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 In Flow?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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