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mhogan2013-9

Ai Image Free

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
99
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0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install ai-image-free
功能描述
generate text or images into AI generated visuals with this skill. Works with JPG, PNG, WebP, MP4 files up to 200MB. content creators use it for generating f...
使用说明 (SKILL.md)

Getting Started

Send me your text or images and I'll handle the AI image generation. Or just describe what you're after.

Try saying:

  • "generate a short text description like 'sunset over a mountain lake' into a 1080p MP4"
  • "generate a free AI image from my description and export it as a video slideshow"
  • "generating free AI images and turning them into video content for content 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.

AI Image Free — Generate and Export AI Images

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

A quick example: upload a short text description like 'sunset over a mountain lake', type "generate a free AI image from my description and export it as a video slideshow", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: simple, specific prompts produce cleaner images and faster results.

Matching Input to Actions

User prompts referencing ai image free, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source ai-image-free
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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.

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

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)

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 → "generate a free AI image from my description and export it as a video slideshow" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a free AI image from my description and export it as a video slideshow" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WebP, MP4 for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.

安全使用建议
This skill mostly does what it says (cloud image/video rendering) and needs one service token (NEMO_TOKEN). Before installing or enabling it: (1) verify the service domain (mega-api-prod.nemovideo.ai) is the official backend you expect; (2) avoid storing a long-lived NEMO_TOKEN in a global environment unless you trust the provider — prefer a limited-scope or anonymous token for testing; (3) confirm whether the skill will access local filesystem paths or only user-uploaded files — the SKILL.md shows examples using local file paths but that should be limited to files the user explicitly uploads; (4) resolve the metadata mismatch about config paths (~/.config/nemovideo/) with the publisher — the registry snapshot lists none but the SKILL.md includes one; and (5) remember that uploads and prompts (including any personal or proprietary media) will be sent to the remote service, so review privacy/terms before sending sensitive content.
功能分析
Type: OpenClaw Skill Name: ai-image-free Version: 1.0.0 The skill is a functional integration for the NemoVideo AI service, enabling image and video generation via a cloud-based GPU pipeline. It communicates exclusively with a dedicated backend (mega-api-prod.nemovideo.ai) using standard REST and SSE protocols. The requested permissions, such as access to the NEMO_TOKEN environment variable and the ~/.config/nemovideo/ directory, are strictly aligned with the stated purpose of session management and authentication. No indicators of data exfiltration, unauthorized execution, or malicious prompt injection were identified.
能力评估
Purpose & Capability
Name and description (generate images/videos) align with the API endpoints and workflows described in SKILL.md. Requesting a single service token (NEMO_TOKEN) is proportionate for a backend service that renders media.
Instruction Scope
The runtime instructions are specific about creating sessions, SSE usage, uploads, and exports to mega-api-prod.nemovideo.ai, which is coherent for a cloud-rendering service. Two items to note: (1) the doc shows multipart uploads using local file paths (e.g., -F "files=@/path"), which implies the agent will accept and forward files — ensure only user-provided files are uploaded, not arbitrary local files; (2) the skill asks to auto-detect X-Skill-Platform from an install path, which may require reading agent or filesystem paths. Neither is obviously malicious, but they broaden what the agent may access.
Install Mechanism
There is no install spec and no code files (instruction-only). That minimizes on-disk persistence and arbitrary code execution risk.
Credentials
The skill requires NEMO_TOKEN as its primary credential which fits the stated purpose. However, there's an inconsistency: the registry metadata provided earlier listed no required config paths, while the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) and primaryEnv. This mismatch should be resolved. Also the skill will create an anonymous token by calling an external API if NEMO_TOKEN isn't present — users should understand the difference between using a permanent token vs an anonymous starter token and avoid putting long-lived secrets in global environments unless they trust the service.
Persistence & Privilege
always is false and there is no installer. The skill does not request persistent system-level privileges. Default autonomous invocation is enabled (platform default) — combine with the single service token and evaluate trust in the remote service before allowing autonomous runs.
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-free
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-image-free 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
AI Image Free — initial release. - Generate AI images and export as MP4, JPG, PNG, WebP, and more (up to 200MB files). - Simple connection process with free starter credits and secure sessions. - Supports text/image input, timeline-based editing, video and slideshow exports. - Fast cloud GPU rendering: get 1080p MP4s in 20–40 seconds. - Clear status updates, automatic error handling, and multi-format export options. - All API requests require attribution headers and handle session/token management automatically.
元数据
Slug ai-image-free
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 Free 是什么?

generate text or images into AI generated visuals with this skill. Works with JPG, PNG, WebP, MP4 files up to 200MB. content creators use it for generating f... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 99 次。

如何安装 Ai Image Free?

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

Ai Image Free 是免费的吗?

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

Ai Image Free 支持哪些平台?

Ai Image Free 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 Free?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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