Maker Ai

create raw footage into polished MP4 videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for automatically crea...

Security Scan

The skill's requests and runtime instructions align with a cloud video-processing service: it only needs a service token, uploads user videos to an external API, and has no install steps or unrelated credential asks.

Purpose & Capability

The name/description (cloud video editing) aligns with the required NEMO_TOKEN and the API endpoints in SKILL.md. Small inconsistency: registry metadata listed no required config paths, but the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) used for metadata — minor mismatch but explainable (metadata vs registry record).

Instruction Scope

Runtime instructions are scoped to the described service (create session, upload files, SSE for edits, export/poll render). They explicitly instruct uploading local files (multipart -F "files=@/path") which is necessary for the stated purpose. One capability to be aware of: the skill derives an X-Skill-Platform header by inspecting common install paths (~/.clawhub, ~/.cursor/skills/) — that implies the agent may check filesystem paths to decide a header value and thus leak which client path was present; this is not needed for core functionality but is low-risk metadata exposure.

Install Mechanism

No install spec and no code files — instruction-only skill (lowest install risk). Nothing is downloaded or written by the skill itself in its spec.

Credentials

Only one credential is requested (NEMO_TOKEN) and it is the token used for API calls. The SKILL.md also documents generating a short-lived anonymous token if no token is present — consistent with a cloud service. No unrelated secrets or multiple credentials are requested.

Persistence & Privilege

Skill is not always-enabled, and it does not request system-wide privileges or to modify other skills. It asks the agent to save a session_id from the API response (expected for session-based APIs) but does not request persistent system-level configuration.

Assessment

This skill appears to do what it says: it uploads your video files to nemovideo's API and returns edited MP4s. Before installing or invoking it, consider: (1) Privacy — your uploaded footage will be sent to https://mega-api-prod.nemovideo.ai; do not upload material you must keep private. (2) Token handling — if you set NEMO_TOKEN in a shared environment, other processes could use it; use the anonymous-token flow if you prefer short-lived access. (3) Optional metadata leakage — the skill may probe common install paths to set an X-Skill-Platform header, which reveals little but non-essential environment info. If you need stronger assurances, ask the publisher for a privacy/data-retention policy and confirm the exact handling of uploaded files and session data.

Getting Started

Ready when you are. Drop your raw footage here or describe what you want to make.

Try saying:

• "create a 2-minute raw screen recording into a 1080p MP4"
• "turn my footage into a polished video with transitions and music"
• "automatically creating edited videos from raw clips for content creators"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Maker AI — Create and Export Finished Videos

Drop your raw footage in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute raw screen recording, ask for turn my footage into a polished video with transitions and music, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter source clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing maker ai, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is maker-ai, 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).

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.

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.

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 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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my footage into a polished video with transitions and music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and devices.

Common Workflows

Quick edit: Upload → "turn my footage into a polished video with transitions and music" → Download MP4. Takes 1-2 minutes 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.