Maker Ai Free

Skip the learning curve of professional editing software. Describe what you want — turn my photos into a 30-second promo video with music and text — and get...

Security Scan

The skill's requested network calls and token usage match a video-rendering service, but small manifest/instruction inconsistencies and the lack of a verifiable source/homepage raise caution before installing or allowing file uploads.

Purpose & Capability

The name/description (AI video creation) align with the runtime instructions: obtaining/using a NEMO_TOKEN, creating sessions, uploading images/videos, running export/render APIs, and polling for results at https://mega-api-prod.nemovideo.ai. Requested capabilities (upload, SSE, render) are proportionate to the stated purpose.

Instruction Scope

SKILL.md gives concrete API flows (anonymous-token, create session, upload, render, poll). It will contact an external backend and upload user media — expected for this purpose. It also instructs detecting install path and reading the skill's YAML frontmatter for attribution (reads local paths like ~/.clawhub/ or ~/.cursor/skills/ and the skill file itself). It does not instruct reading unrelated system secrets or arbitrary files, but it will transmit user files and session tokens to an external service.

Install Mechanism

Instruction-only skill with no install spec and no code files. No binaries or remote downloads are requested, which limits on-disk installation risk.

Credentials

The registry declares NEMO_TOKEN as required/primary (which fits the service). However, SKILL.md explicitly describes auto-generating an anonymous token if NEMO_TOKEN is absent. There is also a mismatch: registry metadata lists no required config paths, but the SKILL.md frontmatter mentions ~/.config/nemovideo/. These manifest/instruction contradictions are inconsistent and could cause unexpected behavior; otherwise only a single service token is requested (proportionate).

Persistence & Privilege

No 'always: true' privilege; default autonomous invocation is allowed (normal). The skill stores session_id for its own requests (expected). It does not request elevated system-wide privileges or modify other skills.

What to consider before installing

This skill appears to be a thin connector to an external video-rendering API and will upload whatever images/videos you provide to https://mega-api-prod.nemovideo.ai. Before installing or invoking it, consider: 1) Sensitivity of files you will upload — do not send private/identifying content unless you trust the service. 2) The manifest is inconsistent: the registry says NEMO_TOKEN is required but the instructions auto-acquire an anonymous token; also SKILL.md references a config path that the registry omitted. These mismatches and the missing homepage/unknown source reduce trust — prefer skills from published vendors or verify the API domain and privacy policy. 3) If you want tighter control, set NEMO_TOKEN to a token/account you control (avoid letting the agent fetch an anonymous token automatically) and review network activity. If you need greater assurance, ask the publisher for a homepage/terms or for the skill to be published by a verified owner.

Getting Started

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

Try saying:

• "create my images or clips"
• "export 1080p MP4"
• "turn my photos into a 30-second"

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 <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. 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 AI Free — Create Videos from Images Free

Send me your images or clips 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 five product photos and a logo file, type "turn my photos into a 30-second promo video with music and text", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer than ten images keeps generation fast and the output focused.

Matching Input to Actions

User prompts referencing maker ai 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.

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

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: maker-ai-free
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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

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

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

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

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

Session state: GET /api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> 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.

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=<id>, 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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my photos into a 30-second promo video with music and text" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.

Export as MP4 for widest compatibility across social platforms and devices.

Common Workflows

Quick edit: Upload → "turn my photos into a 30-second promo video with music and text" → 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.