Free Maker Image

Turn three product photos or a single promotional image into 1080p animated video clips just by typing what you need. Whether it's creating free videos from...

Security Scan

The skill's requests and runtime instructions mostly match its stated purpose (turning images into short videos) and only need a single service token, but there are a few small inconsistencies and privacy/attribution behaviors you should be aware of before installing.

Purpose & Capability

Name and description align with the runtime actions (upload images, create/schedule renders, export MP4). The single required credential NEMO_TOKEN is appropriate for a cloud render API. Minor incoherence: registry metadata listed no required config paths, but the SKILL.md frontmatter declares configPaths (~/.config/nemovideo/) — the skill may attempt to read that path.

Instruction Scope

SKILL.md gives concrete API calls (session creation, SSE, upload, export) and does not instruct reading unrelated system secrets. It does instruct reading the skill's own YAML frontmatter and detecting the agent install path to set X-Skill-Platform — this accesses local path information which is not necessary for video creation and could reveal agent installation layout (privacy concern). It will also obtain an anonymous token automatically if NEMO_TOKEN is absent.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is downloaded or written to disk by an installer. This is the lowest install risk.

Credentials

Only NEMO_TOKEN is required (primaryEnv). That is proportional for a cloud rendering API. Caveat: SKILL.md describes creating/using an anonymous token if NEMO_TOKEN is missing (it posts to a remote endpoint and uses returned token), and the frontmatter references a config path (~/.config/nemovideo/) not listed in the registry metadata — this mismatch should be clarified.

Persistence & Privilege

No always:true flag, no system-wide modifications, no install-time services. The skill runs via API calls and SSE; it does not request persistent elevated agent privileges.

Assessment

This skill appears to do what it says: it calls a remote video-rendering API and needs a single API token (NEMO_TOKEN). Before installing: 1) Confirm the skill's source (homepage is missing) — the frontmatter indicates nemovideo endpoints but the registry owner is an opaque ID. 2) Provide only a throwaway or scoped token if possible; if you don't have NEMO_TOKEN the skill will contact the external API to mint an anonymous token for you. 3) Be aware it may read its own SKILL.md and detect your agent's install path to populate attribution headers — that can leak some local path/installation info. 4) There's a minor metadata mismatch (SKILL.md declares a config path but registry metadata did not); ask the author to clarify whether the skill will read ~/.config/nemovideo/. 5) Because this is instruction-only (no code installed), the main risk is network/privacy exposure to the listed API endpoint — if you trust that service, the skill is coherent; otherwise don't provide production credentials or sensitive tokens.

Getting Started

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

Try saying:

• "create my images"
• "export 1080p MP4"
• "turn my image into a short"

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.

Free Maker Image — Turn Images Into Videos Free

Send me your images 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 or a single promotional image, type "turn my image into a short video with motion and background music", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: high-contrast images with clear subjects produce the best motion effects.

Matching Input to Actions

User prompts referencing free maker 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.

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

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

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

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.

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 Handling

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s once

Common Workflows

Quick edit: Upload → "turn my image into a short video with motion and background music" → 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 "turn my image into a short video with motion and background music" — 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.