Video Trimmer Clideo

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 unwanted sec...

Security Scan

The skill's stated purpose (cloud video trimming) is plausible, but there are inconsistencies in what it requires and how it behaves — notably around token handling, config-path usage, and automatic network actions — that merit caution before installing.

Purpose & Capability

The skill's purpose (trim videos via a cloud backend) matches the described API endpoints and workflows. However, the declared required env/config metadata in the registry is inconsistent with the SKILL.md frontmatter: registry metadata lists no config paths, while the SKILL.md metadata asks for ~/.config/nemovideo/. That mismatch is unexplained and unnecessary for a simple trim workflow.

Instruction Scope

The runtime instructions direct the agent to automatically obtain an anonymous token (POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token) if NEMO_TOKEN is not present, create sessions, upload user files, and persist session IDs. The skill also instructs the agent to suppress showing raw API responses and tokens to users. Automated network calls and credential creation/storage on first use are broader actions than a minimal 'trim on demand' skill and should be explicitly consented to by the user.

Install Mechanism

There is no install spec and no code files — the skill is instruction-only, which reduces filesystem/injection risk. The skill relies on outbound HTTPS requests to a third-party API domain; this is expected for a cloud service integration.

Credentials

Only a single credential (NEMO_TOKEN) is declared, which is proportionate. However, SKILL.md both treats NEMO_TOKEN as required and provides a fallback to generate an anonymous token automatically. That contradiction (declared required vs. on-the-fly creation) is unclear and could lead to unexpected credential storage or lateral use of automatically created tokens.

Persistence & Privilege

The skill instructs storing session_id for subsequent requests and the frontmatter references a user config path (~/.config/nemovideo/). Although always:false and not requesting system-wide privileges, writing to a per-user config directory and persisting tokens/session IDs increases persistence and the blast radius of any misuse. The skill does not explain exactly how/where long-lived credentials are stored or rotated.

What to consider before installing

This skill plausibly does what it says (cloud video trimming) but has inconsistent metadata and asks the agent to create and store tokens and to make automatic network calls. Before installing, consider: 1) Who runs the https://mega-api-prod.nemovideo.ai service and do you trust it? 2) Will the skill write tokens or session IDs to your home config (~/.config/nemovideo/)? Ask the developer to clarify storage location and retention policy. 3) If you prefer control, require that the skill not auto-generate credentials and instead prompt you to provide a token. 4) If possible, run the skill in an environment with restricted outbound network access or review network logs for unexpected activity. If you cannot verify the backend or storage behavior, treat this skill as untrusted.

Getting Started

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

Try saying:

• "trim a 3-minute interview recording with dead air at the start and end into a 1080p MP4"
• "trim the first 20 seconds and cut the last 30 seconds from my video"
• "cutting unwanted sections from video recordings for content creators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Video Trimmer Clideo — Trim and Export Video Clips

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 3-minute interview recording with dead air at the start and end, ask for trim the first 20 seconds and cut the last 30 seconds from my video, 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 and use fewer credits.

Matching Input to Actions

User prompts referencing video trimmer clideo, 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 calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

1. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
2. Chat (SSE) — POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
3. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

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

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

• X-Skill-Source: video-trimmer-clideo
• 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.

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)

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.

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

Common Workflows

Quick edit: Upload → "trim the first 20 seconds and cut the last 30 seconds from my video" → 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 the first 20 seconds and cut the last 30 seconds from my 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.