Ai Screen Recording Editor

edit screen recordings into edited screen recordings with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. educators, developers, content creato...

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud-based screen-recording editing service: it only needs a single service token and uses the remote API to upload, edit, and return videos.

Purpose & Capability

The name/description (AI screen recording editor) align with the actions in SKILL.md: uploading videos, creating sessions, streaming edits, and requesting renders. The declared primary environment variable NEMO_TOKEN is what the remote API expects and is appropriate for this purpose. Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths; this is likely a small metadata mismatch rather than a functional red flag.

Instruction Scope

Instructions are scoped to interacting with the nemovideo.ai backend (auth, session creation, upload, SSE, render, polling). The SKILL.md explicitly limits actions to API calls and streaming; it instructs not to expose raw tokens. It does instruct generating an anonymous token (POST to the service) when NEMO_TOKEN is absent — this is within the skill's remit but important for users to notice because the agent will obtain short-lived credentials automatically.

Install Mechanism

No install step or code files are present (instruction-only), so nothing is written to disk or downloaded. This is the lowest-risk install model and is proportionate to the described cloud-only workflow.

Credentials

Only one credential (NEMO_TOKEN) is required — appropriate for a single third-party service. The skill explicitly supports generating an anonymous short-lived token via the service's anonymous-token endpoint if no token is present; that behavior is reasonable for convenience but means the skill can operate without a user-supplied secret (it will request server-issued credentials). No unrelated secrets or system credentials are requested.

Persistence & Privilege

The skill does not request permanent presence (always:false), has no install steps, and does not ask to modify other skills or system-wide configs. The only slight privilege-like artifact is storing/using a session_id for the editing session (normal for this functionality).

Assessment

This skill appears to do what it says: it uploads videos to a remote renderer (mega-api-prod.nemovideo.ai) and returns edited MP4s. Before installing, consider: 1) you will be sending video/audio to a third-party service — do not upload sensitive or regulated material unless you trust their privacy/retention policies; 2) the skill will use a NEMO_TOKEN if provided, or it will request an anonymous short-lived token from the vendor automatically (100 free credits, 7-day expiry) — be aware that the agent will obtain and use those credentials for uploads and renders; 3) there's a small metadata mismatch (SKILL.md frontmatter mentions a config path that the registry did not list) — not critical but worth noting. If you need to keep recordings private, prefer local editing tools or verify the vendor's terms before use.

Getting Started

Share your screen recordings and I'll get started on AI screen recording editing. Or just tell me what you're thinking.

Try saying:

• "edit my screen recordings"
• "export 1080p MP4"
• "trim the pauses, add zoom effects"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

AI Screen Recording Editor — Edit and Export Screen Recordings

Send me your screen recordings and describe the result you want. The AI screen recording editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute screen recording of a software walkthrough, type "trim the pauses, add zoom effects on click areas, and add captions", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 5 minutes process significantly faster and give more precise AI edits.

Matching Input to Actions

User prompts referencing ai screen recording editor, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

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

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	ai-screen-recording-editor
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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.

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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the pauses, add zoom effects on click areas, and add captions" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best compatibility across platforms and LMS tools.

Common Workflows

Quick edit: Upload → "trim the pauses, add zoom effects on click areas, and add captions" → 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.