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Audio Trimmer

作者 vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install audio-trimmer
功能描述
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...
使用说明 (SKILL.md)

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":"\x3Clang>"}. 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/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"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 \x3CNEMO_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=\x3Cid> (get \x3Cid> 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.

安全使用建议
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.
功能分析
Type: OpenClaw Skill Name: audio-trimmer Version: 1.0.0 The audio-trimmer skill is a legitimate interface for a cloud-based audio processing service hosted at mega-api-prod.nemovideo.ai. It provides detailed instructions for the AI agent to manage sessions, handle file uploads, and trigger rendering tasks via standard API calls. The skill includes appropriate security instructions, such as not exposing tokens to the user, and lacks any indicators of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
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.
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.
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.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install audio-trimmer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /audio-trimmer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Audio Trimmer - Trim and export audio files (MP4, MOV, MP3, WAV, up to 500MB) via cloud GPU processing. - Simple setup: automatic connection and token generation for first-time users. - Supports file upload, silence trimming, clip export (1080p MP4), credits check, and session management. - Handles errors and backend prompts with clear user feedback. - Designed for podcasters, content creators, and students needing fast audio edits.
元数据
Slug audio-trimmer
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Audio Trimmer 是什么?

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... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 47 次。

如何安装 Audio Trimmer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install audio-trimmer」即可一键安装,无需额外配置。

Audio Trimmer 是免费的吗?

是的,Audio Trimmer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Audio Trimmer 支持哪些平台?

Audio Trimmer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Audio Trimmer?

由 vynbosserman65(@vynbosserman65)开发并维护,当前版本 v1.0.0。

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