Free Video Cutter

trim video clips into trimmed video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for cutting long videos...

Security Scan

The skill's declared purpose (cloud video trimming) matches its runtime instructions and required token; the main risks are privacy (uploading video to a third‑party API) and that the skill comes from an unknown source.

Purpose & Capability

Name/description match the actions in SKILL.md: it calls a cloud render API, uploads video files, creates sessions and exports MP4s. The single required env var (NEMO_TOKEN) is consistent with a cloud video backend. Minor mismatch: the registry metadata listed no config paths but the SKILL.md frontmatter references ~/.config/nemovideo/ for config attribution (low-risk inconsistency).

Instruction Scope

Instructions are narrowly scoped to creating sessions, uploading files, running SSE streams, polling job state, and exporting rendered URLs. The skill asks the agent to access local file paths for upload and to probe install paths (~/.clawhub, ~/.cursor/skills/) to emit an X-Skill-Platform header — this is within attribution needs but requires filesystem access and may reveal installed-path information. No instructions are present to read unrelated secrets or system files.

Install Mechanism

No install spec and no code files — instruction-only skill (lowest install risk). Nothing is downloaded or written to disk by an installer in the manifest.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which is appropriate for a cloud API. SKILL.md also documents an anonymous-token bootstrap (POST to /api/auth/anonymous-token) when NEMO_TOKEN is absent — functionally this means the skill will either use a provided token or obtain a short‑lived anonymous token itself. This behavior is coherent but worth noting: the skill can and will contact the remote auth endpoint to obtain tokens if none are present.

Persistence & Privilege

always is false and model invocation is allowed (default). The skill does not request persistent system-wide privileges or attempt to modify other skills. It does require transient access to local files for uploads and to probe install paths for attribution headers.

Assessment

This skill appears to do what it claims (upload clips to a cloud service, run remote trimming, return a download URL). Before installing or using it, consider: 1) Privacy: your video files will be uploaded to https://mega-api-prod.nemovideo.ai — do not upload sensitive or private material unless you trust the service and its retention policy. 2) Token handling: you can supply your own NEMO_TOKEN (preferred) or the skill will obtain an anonymous token automatically; use your own token if you need audit/control. 3) Local access: the skill will need access to file paths you provide for upload and will probe common install paths (~/.clawhub, ~/.cursor/skills/) to set an attribution header — be comfortable with that filesystem probing. 4) Origin: the skill has no homepage and an unknown publisher; if you need stronger assurance, ask the publisher for a privacy policy or audit logs, or test with non-sensitive clips first. 5) If you decide to proceed, monitor network activity (or use a token you can revoke) and avoid uploading content you cannot afford to share with a third party.

Getting Started

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

Try saying:

• "trim my video clips"
• "export 1080p MP4"
• "cut out the first 2 minutes"

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.

Free Video Cutter — Cut and Export Video Clips

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

A quick example: upload a 10-minute interview recording, type "cut out the first 2 minutes and trim the ending after the 7-minute mark", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: shorter source clips process faster and use fewer credits.

Matching Input to Actions

User prompts referencing free video cutter, 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.

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

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

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 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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut out the first 2 minutes and trim the ending after the 7-minute mark" — 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.

Common Workflows

Quick edit: Upload → "cut out the first 2 minutes and trim the ending after the 7-minute mark" → Download MP4. Takes 20-40 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.