Screen Recording Editor Free

Skip the learning curve of professional editing software. Describe what you want — trim the pauses, add text annotations, and export as a clean tutorial vide...

Security Scan

The skill's declared requirements and runtime instructions align with its stated purpose (remote AI-based video editing); it asks for one service token and uploads user media to the remote API as expected.

Purpose & Capability

Name/description (cloud-based screen-recording editing) matches the requested environment variable (NEMO_TOKEN) and declared config path (~/.config/nemovideo/). All required items are consistent with a service that performs remote rendering and needs a session/token.

Instruction Scope

Instructions direct the agent to authenticate (use or fetch NEMO_TOKEN), create a session, upload video files (up to 500MB) and stream SSE responses from the service — this is expected for a remote editor. Two points to be aware of: (1) user media and metadata will be transmitted to a third-party endpoint (mega-api-prod.nemovideo.ai), and (2) the skill asks the agent to derive X-Skill-Platform from install paths (e.g., ~/.clawhub/) which could leak local path/context if implemented naively. Neither is incoherent with the stated purpose, but both are privacy-relevant.

Install Mechanism

No install spec and no code files — runtime behavior is entirely instruction-driven and uses HTTPS endpoints. This lowers risk from arbitrary install scripts or downloaded executables.

Credentials

Only a single service credential (NEMO_TOKEN) is required and is exactly the kind of secret expected for a hosted rendering API. The SKILL.md also documents creating an anonymous token if one isn't provided, which is consistent with a consumer-facing service.

Persistence & Privilege

Skill is not always-enabled and does not request elevated or persistent system privileges. It instructs saving session_id locally for tracking jobs (normal for a session-based API).

Assessment

This skill will upload your video/audio files and related job metadata to a third-party API (mega-api-prod.nemovideo.ai) and requires a service token (NEMO_TOKEN). Before installing or using it: (1) confirm you trust the service and understand its privacy/retention policy if you plan to upload sensitive recordings, (2) prefer using an anonymous token or throwaway account for testing, and avoid providing highly sensitive content until you verify storage/retention and access controls, (3) be aware the skill adds headers that may include a detected install-path/platform value — that could reveal local path context, so review how your agent/runtime implements that header, and (4) watch for any UI that prints tokens or raw JSON; the SKILL.md says not to print tokens, but verify the agent respects that. Overall the skill appears coherent with its purpose.

Getting Started

Ready when you are. Drop your screen recordings here or describe what you want to make.

Try saying:

• "edit a 3-minute screen recording of a software tutorial into a 1080p MP4"
• "trim the pauses, add text annotations, and export as a clean tutorial video"
• "trimming and polishing screen recordings for tutorials or demos for educators, developers, 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.

Screen Recording Editor Free — Edit and Export Screen Recordings

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

A quick example: upload a 3-minute screen recording of a software tutorial, type "trim the pauses, add text annotations, and export as a clean tutorial video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: splitting long recordings into shorter segments speeds up processing significantly.

Matching Input to Actions

User prompts referencing screen recording editor free, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is screen-recording-editor-free, 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.

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.

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

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)

Common Workflows

Quick edit: Upload → "trim the pauses, add text annotations, and export as a clean tutorial 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 "trim the pauses, add text annotations, and export as a clean tutorial 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 across platforms and devices.