Editor Filters

Skip the learning curve of professional editing software. Describe what you want — apply a cinematic color grade filter and smooth skin tone across the whole...

Security Scan

The skill's declared purpose (cloud video filtering) matches its network activity and single required credential (NEMO_TOKEN), but there are inconsistent metadata & instruction details and some minor scope creep (filesystem/install-path inference and hidden technical steps) that warrant caution before installing.

Purpose & Capability

The name/description (apply cinematic filters, export videos) align with the API endpoints and flows described in SKILL.md. Requesting a single service token (NEMO_TOKEN) is proportionate to a cloud rendering service. However, SKILL.md frontmatter references a config path (~/.config/nemovideo/) whereas the registry metadata provided earlier listed no required config paths — this mismatch is an inconsistency worth noting.

Instruction Scope

The runtime instructions tell the agent to upload user video files and call many backend endpoints at mega-api-prod.nemovideo.ai — which is expected for this service. Concerns: (1) the instructions ask the agent to derive X-Skill-Platform from the install path (e.g., check ~/.clawhub/ or ~/.cursor/skills/), which implies filesystem inspection beyond strictly sending videos; (2) the SKILL.md explicitly instructs to hide technical details from the user ('Keep the technical details out of the chat'), which reduces transparency about background network activity to end users. Otherwise, the explicit API calls, SSE handling, and token-refresh flow are within the claimed editing purpose.

Install Mechanism

This is instruction-only with no install spec and no code files, so nothing will be written to disk by an installer. That lowers install risk.

Credentials

The skill requires a single credential: NEMO_TOKEN (primaryEnv). That is proportionate for a cloud video editing service. Minor inconsistency: SKILL.md frontmatter references a config path (~/.config/nemovideo/) which could imply reading local config, though the registry metadata at the top said 'Required config paths: none'. There are no other unrelated secrets requested.

Persistence & Privilege

always:false and default autonomous invocation are set. The skill does not request permanent/always-on presence or modify other skills' config. Autonomous invocation is the platform default; no extra privilege is requested.

What to consider before installing

This skill is broadly consistent with a cloud video-editing service, but review a few things before installing or using it: - Understand data flow: your video files will be uploaded to https://mega-api-prod.nemovideo.ai and processed there. Confirm the service's privacy/storage policy before sending sensitive videos. - Credential choice: you can supply a NEMO_TOKEN or the skill will mint an anonymous token by POSTing to the service. Do not provide other unrelated credentials. - Metadata mismatch: SKILL.md mentions a local config path (~/.config/nemovideo/) and also instructs deriving an install-path-based header; ask the publisher why the skill needs to inspect local paths or configs. If you don't want the agent checking filesystem paths, decline installation or request a version without that behavior. - Transparency: the skill instructs the agent to hide technical details from users; insist on clear user-visible status messages when uploads or charges/credits occur. If you decide to proceed: only provide NEMO_TOKEN if you trust the service, avoid supplying other secrets, and consider testing with non-sensitive short clips first. If you can, request the publisher's homepage or privacy/terms to validate the third-party domain.

Getting Started

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

Try saying:

• "edit my video clips"
• "export 1080p MP4"
• "apply a cinematic color grade filter"

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.

Editor Filters — Apply Filters and Export Videos

This tool takes your video clips and runs AI filter application through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute vlog recorded on a smartphone and want to apply a cinematic color grade filter and smooth skin tone across the whole clip — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process filters significantly faster.

Matching Input to Actions

User prompts referencing editor filters, 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 editor-filters, 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).

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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)

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

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.

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 → "apply a cinematic color grade filter and smooth skin tone across the whole clip" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "apply a cinematic color grade filter and smooth skin tone across the whole clip" — 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.