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Maker Free Image

作者 susan4731-wilfordf · 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 maker-free-image
功能描述
create images or text into image-based videos with this skill. Works with JPG, PNG, WebP, GIF files up to 200MB. content creators and marketers use it for cr...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "create my images or text"
  • "export 1080p MP4"
  • "turn these images into a short"

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.

Maker Free Image — Create Videos From Images Free

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

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

Worth noting: using fewer high-quality images produces cleaner output than many low-res ones.

Matching Input to Actions

User prompts referencing maker free image, 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: maker-free-image
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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)

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 → "turn these images into a short video with music and transitions" → 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 images into a short video with music and transitions" — 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 appears aligned with its stated cloud video-generation purpose. Before installing, be comfortable with sending your images, prompts, and other media to mega-api-prod.nemovideo.ai, and protect the NEMO_TOKEN because it controls the service session and credits.
功能分析
Type: OpenClaw Skill Name: maker-free-image Version: 1.0.0 The skill provides instructions for an AI agent to interface with a cloud-based video generation service at mega-api-prod.nemovideo.ai. It outlines standard procedures for anonymous authentication (generating a UUID), session management, and API interactions for uploading media and rendering videos. While it includes logic to detect the host platform (e.g., Cursor or Clawhub) for attribution headers, its behavior is consistent with its stated purpose and lacks indicators of malicious intent or data exfiltration.
能力评估
Purpose & Capability
The described capabilities match the stated purpose: create/export image-based videos via a remote GPU service. The main user-visible risk is that uploaded images, text, and media are processed by a third-party API.
Instruction Scope
The skill includes automation instructions that translate backend GUI-style responses into API actions, including export. This appears purpose-aligned but users should watch for unexpected actions or credit use.
Install Mechanism
No install spec or code files are present, so there is no local executable installer to review. The skill is instruction-only.
Credentials
The required NEMO_TOKEN and remote API access are proportionate for a cloud rendering service, and token handling is disclosed.
Persistence & Privilege
The skill stores a session_id for later requests and uses a token valid for 7 days, but the provided artifacts do not show hidden background execution or persistent local code.
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 maker-free-image
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /maker-free-image 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 — turn images or text into videos using cloud GPU processing, no paid software needed. - Supports JPG, PNG, WebP, GIF uploads up to 200MB; outputs 1080p MP4. - Automated connection flow: free NEMO_TOKEN issued for new users (valid 7 days, 100 free credits). - User-friendly commands for export, credit balance, state, and uploads. - Fast cloud video rendering (30–60 seconds typical), with full session and job management. - Built-in error codes and handling for smoother troubleshooting. - Designed for content creators and marketers needing quick, free video generation.
元数据
Slug maker-free-image
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

Maker Free Image 是什么?

create images or text into image-based videos with this skill. Works with JPG, PNG, WebP, GIF files up to 200MB. content creators and marketers use it for cr... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 57 次。

如何安装 Maker Free Image?

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

Maker Free Image 是免费的吗?

是的,Maker Free Image 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Maker Free Image 支持哪些平台?

Maker Free Image 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 Maker Free Image?

由 susan4731-wilfordf(@susan4731-wilfordf)开发并维护,当前版本 v1.0.0。

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