Video Trimmer Free

Skip the learning curve of professional editing software. Describe what you want — trim out the first 2 minutes and cut the section from 5:30 to 6:00 — and g...

Security Scan

The skill's requirements and runtime instructions align with a cloud video-trimming service: it needs a NEMO_TOKEN and uploads user video to nemo's API — nothing requested appears disproportionate to that purpose, though it will send user data to a third party and a small metadata inconsistency should be clarified.

Purpose & Capability

Name/description (video trimming) match the declared primary credential NEMO_TOKEN and the SKILL.md's endpoints at mega-api-prod.nemovideo.ai. The only inconsistency: registry-level metadata reported "Required config paths: none", but the skill's YAML frontmatter declares a config path (~/.config/nemovideo/) in metadata.requires; this is likely an authoring oversight but should be clarified.

Instruction Scope

SKILL.md instructs the agent to create a session, upload user-sent video files, stream SSE messages, and poll export endpoints — all coherent for a cloud render pipeline. It also instructs reading the skill's YAML frontmatter for attribution headers and detecting install path to set X-Skill-Platform; these are reasonable but imply filesystem access to the skill file and possibly to the agent's home directory to detect an install path.

Install Mechanism

Instruction-only skill with no install spec and no code files. This is the lowest-risk install pattern; nothing is downloaded or extracted.

Credentials

Only NEMO_TOKEN is required (primaryEnv). The SKILL.md provides a fallback anonymous-token acquisition flow if the token is absent. No unrelated credentials, secrets, or multiple tokens are requested.

Persistence & Privilege

always is false and the skill does not request elevated or permanent presence. It does instruct the agent to create short-lived sessions with the backend but does not attempt to modify other skills or system-wide settings.

Assessment

This skill appears to do what it says: it uploads videos to nemo's cloud service and returns trimmed outputs. Before installing, confirm you're comfortable uploading any videos you send (sensitive content may be exposed to the third party). Note the skill needs a NEMO_TOKEN (or will request an anonymous token on your behalf) — avoid reusing long-lived tokens from other services; use a dedicated token if possible. Ask the publisher to clarify the config-path declaration (~/.config/nemovideo/) vs. the registry metadata mismatch, and verify the service's privacy/retention policy at the API domain (mega-api-prod.nemovideo.ai) if you handle private material.

Getting Started

Send me your video clips and I'll handle the AI video trimming. Or just describe what you're after.

Try saying:

• "trim a 10-minute raw screen recording into a 1080p MP4"
• "trim out the first 2 minutes and cut the section from 5:30 to 6:00"
• "cutting unwanted sections from raw video footage for content creators"

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.

Video Trimmer Free — Trim and Export Clean Videos

Drop your video clips in the chat and tell me what you need. I'll handle the AI video trimming on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 10-minute raw screen recording, ask for trim out the first 2 minutes and cut the section from 5:30 to 6:00, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter source clips process faster — split long videos before uploading if possible.

Matching Input to Actions

User prompts referencing video trimmer 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.

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.

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

• X-Skill-Source: video-trimmer-free
• 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

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

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 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)

Common Workflows

Quick edit: Upload → "trim out the first 2 minutes and cut the section from 5:30 to 6:00" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim out the first 2 minutes and cut the section from 5:30 to 6:00" — 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.