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Audio Trimmer Online

v1.0.0

Skip the learning curve of professional editing software. Describe what you want — trim the first 15 seconds and cut everything after the 2-minute mark — and...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for linmillsd7/audio-trimmer-online.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Audio Trimmer Online" (linmillsd7/audio-trimmer-online) from ClawHub.
Skill page: https://clawhub.ai/linmillsd7/audio-trimmer-online
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install audio-trimmer-online

ClawHub CLI

Package manager switcher

npx clawhub@latest install audio-trimmer-online
Security Scan
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Purpose & Capability
The skill's name and description match a cloud-based audio trimming service and the only declared credential (NEMO_TOKEN) is relevant. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — an inconsistency in declared requirements.
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Instruction Scope
Runtime instructions tell the agent to check for NEMO_TOKEN, and if absent to POST to an external anonymous-token endpoint to obtain a token; create sessions; upload user files; poll render jobs; and read install/config paths to set attribution headers. These actions are coherent with a cloud render service but they include filesystem checks (install path and optional config directory) and automatic token acquisition which broadens the agent's runtime behavior beyond simply forwarding a user file to a remote API.
Install Mechanism
There is no install spec and no code files (instruction-only), so nothing is written to disk by the skill package itself. This is the lowest install risk.
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Credentials
The only declared credential is NEMO_TOKEN which is appropriate for a cloud API. But the SKILL.md both expects that env var and instructs creating/using an anonymous token via the remote endpoint if it's missing. The frontmatter's advertised config path (~/.config/nemovideo/) suggests the skill may read local config files to find tokens — the registry said no config paths — this mismatch and the token-acquisition behavior merit attention because tokens grant upload/export privileges to the remote service.
Persistence & Privilege
always:false and no instructions to modify other skills or system-wide settings. The skill creates short-lived sessions on the backend and may orphan render jobs if the session closes, but it does not request forced persistent installation or escalated privileges.
What to consider before installing
This skill appears to implement a cloud audio-trimming service — it will upload your audio to https://mega-api-prod.nemovideo.ai, create a session, and use a NEMO_TOKEN to perform uploads and exports. Before installing, consider: 1) There is no homepage or owner information — verify the service identity and privacy policy. 2) The skill may read local install/config paths (~/.clawhub, ~/.cursor/skills/, and ~/.config/nemovideo/) to set headers or locate tokens — ensure you’re comfortable with that filesystem access. 3) If you don’t provide NEMO_TOKEN, the skill will call the anonymous-token endpoint to obtain a temporary token (100 free credits, 7-day expiry) — understand that this results in network calls and short-lived credentials being issued. 4) The skill will upload audio to a remote service — do not send sensitive or private audio unless you trust the backend. 5) Confirm where (if anywhere) the token will be stored by your agent/runtime; tokens enable exports/uploads. 6) The registry metadata and the SKILL.md frontmatter disagree about required config paths — ask the publisher to clarify. If you proceed, prefer testing with non-sensitive files and monitor network activity and token storage.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

✂️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk972kz2f565pvvw1d506096c1185k5rc
36downloads
0stars
1versions
Updated 1d ago
v1.0.0
MIT-0

Getting Started

Send me your audio files and I'll handle the audio trimming editing. Or just describe what you're after.

Try saying:

  • "trim a 3-minute podcast recording with dead air at the start and end into a 1080p MP4"
  • "trim the first 15 seconds and cut everything after the 2-minute mark"
  • "cutting unwanted sections from audio recordings for podcasters, content creators, students"

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.

Audio Trimmer Online — Trim and Export Audio Clips

This tool takes your audio files and runs audio trimming editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute podcast recording with dead air at the start and end and want to trim the first 15 seconds and cut everything after the 2-minute mark — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.

Tip: shorter audio files under 60 seconds process almost instantly.

Matching Input to Actions

User prompts referencing audio trimmer online, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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: audio-trimmer-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 Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the first 15 seconds and cut everything after the 2-minute mark" — concrete instructions get better results.

Max file size is 200MB. Stick to MP3, WAV, AAC, M4A for the smoothest experience.

Export as MP3 for widest compatibility across devices and platforms.

Common Workflows

Quick edit: Upload → "trim the first 15 seconds and cut everything after the 2-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.

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