Ai Video Editor Eraser

Get clean erased clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "erase...

Security Scan

The skill's requests and runtime instructions align with a remote video-editing API: it asks for one service token (NEMO_TOKEN) or obtains an anonymous token and describes calling the nemo video API; there are minor metadata mismatches but no disproportionate privileges or unrelated credential requests.

Purpose & Capability

The name/description match the runtime instructions: the SKILL.md details uploading videos, creating sessions, sending SSE messages, and exporting rendered MP4s via the nemo video API. Required env var (NEMO_TOKEN) is appropriate for a hosted API. Minor inconsistency: the registry metadata listed no config paths but the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/). This is a small metadata mismatch rather than a functional problem.

Instruction Scope

The instructions are scoped to the stated purpose: create a session, upload files, send editing messages, poll export status, and return download URLs. They do not instruct reading arbitrary local files or unrelated environment variables. The only network calls described target the nemo-video API endpoints.

Install Mechanism

No install spec or code files are present (instruction-only). Nothing is written to disk or downloaded by the skill itself per the package contents, which is the lowest-risk install profile.

Credentials

Only one credential is requested (NEMO_TOKEN), which is proportional to a hosted video-editing service. The SKILL.md also documents an anonymous-token fallback obtained via an anonymous-token endpoint when NEMO_TOKEN is missing. That fallback is reasonable, but users should confirm what privileges their NEMO_TOKEN grants before supplying it (see guidance).

Persistence & Privilege

always:false and default model invocation are appropriate. The skill uses ephemeral session tokens for jobs; it does not request persistent system-wide privileges or attempt to modify other skills or agent settings.

Assessment

This skill appears to do what it says: it uploads your video to a remote nemo-video service and returns edited downloads. Before installing, consider: (1) Source is unknown—verify you trust the service and owner before providing any long-lived token. (2) Supplying NEMO_TOKEN gives the skill bearer whatever rights that token contains; if that token is reused across other services, do not share it. Use the anonymous-token fallback if you prefer not to disclose credentials. (3) Your videos (and any metadata) will be uploaded to the remote API—don’t upload sensitive material you wouldn’t want sent to an external service. (4) The package metadata has a small mismatch around configPaths in SKILL.md vs registry; this is minor but you can ask the publisher to clarify origin and intended config access.

Getting Started

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

Try saying:

• "edit a 30-second clip with an unwanted logo in the corner into a 1080p MP4"
• "erase the watermark from the bottom-right corner of my video"
• "removing unwanted objects or watermarks from video footage 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 Video Editor Eraser — Erase Objects from Videos

Send me your video clips and describe the result you want. The AI object removal runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 30-second clip with an unwanted logo in the corner, type "erase the watermark from the bottom-right corner of my video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips with static backgrounds produce cleaner erase results.

Matching Input to Actions

User prompts referencing ai video editor eraser, 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-video-editor-eraser
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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 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

Common Workflows

Quick edit: Upload → "erase the watermark from the bottom-right corner of my video" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "erase the watermark from the bottom-right corner of my video" — 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.