Video Test Udnerc

Get processed test video ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something lik...

Security Scan

The skill's stated purpose (cloud video test renders) matches most of its runtime instructions, but there are inconsistencies about config/storage and the skill will automatically obtain and persist tokens and upload user video files to an external service — things you should verify before installing or using it.

Purpose & Capability

Name/description, endpoints and actions all align with a cloud video-processing skill. Requesting a NEMO_TOKEN credential is expected. However, the SKILL.md metadata references a config path (~/.config/nemovideo/) for storage even though the skill registry metadata listed no required config paths — that's an internal inconsistency and suggests the skill intends to persist state on disk.

Instruction Scope

Instructions remain within video-processing scope (create session, upload video, poll export, read SSE). They explicitly instruct generating an anonymous token if NEMO_TOKEN is absent and storing session_id for subsequent calls. This means the agent will contact an external domain and upload user-provided video files; that is expected for this service but is notable: user content and tokens will be sent off-host. The doc also instructs the agent not to display raw API responses or tokens to users, which limits visibility into what is being stored/transmitted.

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk. Nothing is downloaded or written by an installer step described in the registry.

Credentials

The only declared environment credential is NEMO_TOKEN (primaryEnv), which is reasonable. However, SKILL.md metadata includes a config path (~/.config/nemovideo/) and the instructions instruct generating and storing anonymous tokens/session IDs if NEMO_TOKEN is missing. The registry did not declare config path requirements earlier — mismatch. Persisting tokens/session state to disk without declaring it is disproportionate to what was advertised and reduces transparency.

Persistence & Privilege

always:false and no autonomous-invocation override — ordinary. But the skill's instructions explicitly create and persist anonymous tokens and session IDs and reference a user config directory; this implies on-disk persistence of credentials and job state. That persistence is not announced in the registry metadata and could be surprising to users.

What to consider before installing

This skill appears to truly be a cloud video test-render helper, but it will upload any video you give it to https://mega-api-prod.nemovideo.ai and will generate or use a NEMO_TOKEN for authorization. Before using/installing: (1) Be aware that your videos and a session token may be sent to and stored by an external service. (2) The SKILL.md references writing/reading ~/.config/nemovideo/ but the registry didn't declare that — ask the publisher where session/tokens are stored and whether they are kept on disk. (3) If you want more control, set your own NEMO_TOKEN rather than letting the skill auto-create one, and avoid uploading sensitive content until you verify the service/privacy policy. (4) Because the skill's source/homepage is unknown, prefer caution: confirm the service domain and privacy/security practices or only use test/non-sensitive footage.

Getting Started

Got raw video footage to work with? Send it over and tell me what you need — I'll take care of the AI video testing.

Try saying:

• "test a 30-second test recording from a webcam into a 1080p MP4"
• "run a test render to check quality and playback settings"
• "testing video render quality before final export for video creators"

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.

Video Test Render — Test and Export Video Files

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

Here's a typical use: you send a a 30-second test recording from a webcam, ask for run a test render to check quality and playback settings, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips process faster and are ideal for quick test renders.

Matching Input to Actions

User prompts referencing video test udnerc, 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. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. 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. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is video-test-udnerc, 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).

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

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

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.

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

Common Workflows

Quick edit: Upload → "run a test render to check quality and playback settings" → 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 "run a test render to check quality and playback settings" — 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.