Audio Trimmer

v1.0.0

trim audio files into trimmed audio clips with this skill. Works with MP4, MOV, MP3, WAV files up to 500MB. podcasters, content creators, students use it for...

⭐ 0· 38·0 current·0 all-time

by@vynbosserman65

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for vynbosserman65/audio-trimmer.

Previewing Install & Setup.

Prompt PreviewInstall & Setup

Install the skill "Audio Trimmer" (vynbosserman65/audio-trimmer) from ClawHub.
Skill page: https://clawhub.ai/vynbosserman65/audio-trimmer
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

ClawHub CLI

Package manager switcher

npx clawhub@latest install audio-trimmer

Security Scan

VirusTotal

Benign

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OpenClaw

Suspicious

medium confidence

ℹ

Purpose & Capability

The name/description (trim and export audio) aligns with the runtime instructions: the skill uploads user audio to a cloud rendering backend and returns edited MP4s. Requiring a NEMO_TOKEN for the backend is proportionate. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata listed no required config paths — this inconsistency should be resolved.

ℹ

Instruction Scope

The instructions are explicit about network operations: checking NEMO_TOKEN, obtaining an anonymous token if absent, creating sessions, uploading files, using SSE, and polling a render endpoint. All of that is expected for a cloud-based trimmer. The skill does not instruct reading unrelated system files, but it references auto-detecting platform from install path and a config path in frontmatter — verify whether the agent will access ~/.config/nemovideo/ or other local paths.

✓

Install Mechanism

There is no install spec and no code files (instruction-only). That minimizes on-disk installation risk; runtime risk is limited to the described network calls.

ℹ

Credentials

The only declared credential is NEMO_TOKEN (primaryEnv), which is appropriate for a hosted processing service. The skill also includes steps to obtain an anonymous token if NEMO_TOKEN is absent. This is reasonable, but be aware that supplying NEMO_TOKEN grants the skill bearer access to whatever account/credits that token controls. The frontmatter's configPath requirement (present in SKILL.md) is not reflected in the registry’s declared requirements — that mismatch is unexpected.

✓

Persistence & Privilege

The skill is not always-enabled and does not request system-wide changes. It keeps a session_id per use (normal for remote jobs). It does not request elevated system privileges or to modify other skills.

What to consider before installing

This skill behaves like a typical cloud audio editor: it will upload whatever you give it to an external domain (mega-api-prod.nemovideo.ai) and use a NEMO_TOKEN for account/auth. Things to consider before installing: 1) The skill has no source code or homepage listed — you have limited provenance to trust the backend. 2) Decide whether you are comfortable uploading potentially sensitive audio to this unknown service. 3) If you provide a NEMO_TOKEN, it can be used to access that account — prefer a dedicated/test token or use the anonymous flow instead. 4) Ask the publisher to clarify the config path discrepancy (~/.config/nemovideo/) and to provide a homepage or source repo and privacy/retention policy. 5) Test first with non-sensitive, short files. If you need higher assurance, prefer skills with verifiable source and a known operator.

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

Runtime requirements

✂️ Clawdis

EnvNEMO_TOKEN

Primary envNEMO_TOKEN

latestvk973ganf83yf0q0d99r6cnvvfh85n9p8

38downloads

0stars

1versions

Updated 14h ago

v1.0.0

MIT-0

Getting Started

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

Try saying:

"trim my audio files"
"export 1080p MP4"
"trim the silence at the start"

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 — Trim and Export Audio Clips

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

A quick example: upload a 10-minute podcast recording with long pauses, type "trim the silence at the start and cut the last 2 minutes of dead air", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: shorter audio files process faster — split long recordings before uploading if possible.

Matching Input to Actions

User prompts referencing audio trimmer, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
`/api/tasks/me/with-session/nemo_agent`	POST	Start a new editing session. Body: `{"task_name":"project","language":"<lang>"}`. Returns `session_id`.
`/run_sse`	POST	Send a user message. Body includes `app_name`, `session_id`, `new_message`. Stream response with `Accept: text/event-stream`. Timeout: 15 min.
`/api/upload-video/nemo_agent/me/<sid>`	POST	Upload a file (multipart) or URL.
`/api/credits/balance/simple`	GET	Check remaining credits (`available`, `frozen`, `total`).
`/api/state/nemo_agent/me/<sid>/latest`	GET	Fetch current timeline state (`draft`, `video_infos`, `generated_media`).
`/api/render/proxy/lambda`	POST	Start export. Body: `{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll status every 30s.

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

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
`X-Skill-Source`	`audio-trimmer`
`X-Skill-Version`	frontmatter `version`
`X-Skill-Platform`	auto-detect: `clawhub` / `cursor` / `unknown` from install path

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

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.

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

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 silence at the start and cut the last 2 minutes of dead air" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, MP3, WAV for the smoothest experience.

Export as MP4 for widest compatibility when embedding audio in video projects.

Common Workflows

Quick edit: Upload → "trim the silence at the start and cut the last 2 minutes of dead air" → 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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