Screen Recording Online

edit screen recordings into polished screen recordings with this screen-recording-online skill. Works with MP4, MOV, WebM, AVI files up to 500MB. educators,...

Security Scan

The skill's declared requirements and runtime instructions align with a cloud-based video-editing integration that uses a single NEMO_TOKEN credential and makes API calls to nemovideo.ai; nothing requested appears disproportionate to that purpose.

Purpose & Capability

Name/description advertise cloud video editing; the skill only requests a single service token (NEMO_TOKEN) and references a nemovideo API domain. Those requirements are coherent with a remote video-processing service.

Instruction Scope

SKILL.md instructs the agent to create sessions, upload files, perform SSE-based edits, poll render status, and return download URLs — all consistent with a remote render pipeline. It also instructs the agent to detect install path and read the skill's YAML frontmatter and a declared config path (~/.config/nemovideo/) for attribution; these filesystem checks are reasonable for attribution but do require filesystem access and should be expected. The skill also documents anonymous-token acquisition if NEMO_TOKEN is absent; that means the agent will make network POSTs to obtain a token.

Install Mechanism

Instruction-only skill (no install spec, no code files). No packages or downloads are installed by the skill itself, minimizing disk-write risk.

Credentials

Only one credential is declared (NEMO_TOKEN) and the SKILL.md describes how it is used (Bearer auth for API calls). The frontmatter additionally lists a config path (~/.config/nemovideo/) which aligns with the service. No unrelated credentials or broad environment access are requested.

Persistence & Privilege

always is false and the skill does not request or document modifying other skills or system-wide settings. It does create in-memory session IDs and uses tokens for the remote service, which is normal for this type of integration.

Assessment

This skill appears to do what it says: it uploads user video files to an external service (mega-api-prod.nemovideo.ai) for server-side editing and returns download links. Before installing, consider: (1) Privacy — any video you provide will be sent to that external API; do not upload sensitive recordings unless you trust the service and its policy. (2) Tokens — the skill uses NEMO_TOKEN (or will request an anonymous token) to authenticate; keep only tokens you are comfortable exposing to the agent. (3) Filesystem checks — the skill may check declared config paths and the install path for attribution headers, which requires limited filesystem access. (4) Verify the API domain and organization — the skill metadata has no homepage or known owner; if you need higher assurance, confirm the service's legitimacy (official docs, privacy policy) before providing videos or credentials. Autonomous invocation is allowed by default; if you want to limit automatic uploads, restrict agent permissions or avoid granting NEMO_TOKEN to the environment.

Getting Started

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

Try saying:

• "edit a 3-minute browser screen recording into a 1080p MP4"
• "trim the pauses, add captions, and export as MP4"
• "editing and sharing screen recordings online for educators, developers, marketers"

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.

Screen Recording Online — Edit and Share Screen Recordings

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

A quick example: upload a 3-minute browser screen recording, type "trim the pauses, add captions, and export as MP4", 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.

Matching Input to Actions

User prompts referencing screen recording online, 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.

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: screen-recording-online
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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

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.

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 captions, and export as MP4" → 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 captions, and export as MP4" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and devices.