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vcarolxhberger

Generator From Audio

by vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install generator-from-audio
Description
generate audio files into audio-driven videos with this skill. Works with MP3, WAV, AAC, M4A files up to 200MB. podcasters, content creators, marketers use i...
README (SKILL.md)

Getting Started

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

Try saying:

  • "generate my audio files"
  • "export 1080p MP4"
  • "turn this audio into a video"

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 \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. 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.

Generator From Audio — Turn Audio Into Shareable Videos

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

Say you have a 2-minute podcast audio recording and want to turn this audio into a video with waveform visuals and captions — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter audio clips under 60 seconds produce the fastest results.

Matching Input to Actions

User prompts referencing generator from audio, 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.

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is generator-from-audio, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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

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

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

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)

Common Workflows

Quick edit: Upload → "turn this audio into a video with waveform visuals and captions" → Download MP4. Takes 1-2 minutes 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 "turn this audio into a video with waveform visuals and captions" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across YouTube, Instagram, and TikTok.

Usage Guidance
This skill is coherent for converting audio to video via the nemo backend, but it will: (1) upload your audio to https://mega-api-prod.nemovideo.ai for cloud processing; (2) generate or use an auth token (it can auto-create an anonymous token tied to a generated client UUID) and will store session IDs/tokens for subsequent requests; and (3) may read install/config paths to set attribution headers. Before installing, decide whether you are comfortable with your audio being sent to that external service and with the skill storing tokens/sessions (local or remote). If you prefer tighter control: set NEMO_TOKEN yourself rather than allowing anonymous token creation, avoid uploading sensitive audio, and verify the service's privacy/retention policy. Also note the skill’s source/homepage is unknown — exercise normal caution with unvetted skills.
Capability Analysis
Type: OpenClaw Skill Name: generator-from-audio Version: 1.0.0 The 'generator-from-audio' skill is a legitimate integration for an AI video creation service (nemovideo.ai). The SKILL.md file provides clear instructions for the agent to manage authentication via anonymous tokens, handle session states, and interact with the service's API for uploading audio and exporting video. While it performs environment detection (e.g., checking install paths like ~/.cursor/skills/) and requires network access, these actions are directly aligned with its stated purpose of cloud-based video rendering and do not exhibit signs of malicious intent, data exfiltration, or unauthorized system access.
Capability Assessment
Purpose & Capability
Name/description match the required credential and API calls: the skill converts audio to video through the nemo video service and therefore legitimately needs a NEMO_TOKEN and endpoints under nemovideo.ai. Required env var (NEMO_TOKEN) is proportionate to the stated purpose.
Instruction Scope
SKILL.md tells the agent to perform network operations (obtain anonymous token, create session, upload files, start exports, poll render status) and to upload user audio to the remote backend — which is expected for this service. It also instructs generating/storing anonymous tokens and detecting install paths to set an X-Skill-Platform header; detection implies reading certain filesystem paths. These actions are within the skill's purpose but involve transmitting user files and storing tokens, so be aware of data exfiltration/retention choices.
Install Mechanism
No install spec or bundled code — this is instruction-only, so nothing is written to disk by an installer. That minimizes supply-chain risk, though runtime network calls are required.
Credentials
Only one credential (NEMO_TOKEN) is declared and used. The skill also offers to generate an anonymous token if NEMO_TOKEN is absent; this is consistent with the backend's auth model. Metadata mentions a config path (~/.config/nemovideo/) but the instructions primarily check the environment variable — minor mismatch but not disproportionate.
Persistence & Privilege
always:false (no forced presence). The skill instructs storing a session_id/token for subsequent requests and metadata lists a config path; that implies the agent may persist credentials or session state locally. This is plausible for convenience but users should be aware tokens/sessions may be written to disk or retained by the remote service.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install generator-from-audio
  3. After installation, invoke the skill by name or use /generator-from-audio
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Generator From Audio: turn audio files into shareable videos using a fast cloud rendering pipeline. - Supports MP3, WAV, AAC, M4A files up to 200MB; produces 1080p MP4s in about 1-2 minutes. - Automatic backend connection and authentication with 100 free credits for new users. - Handles uploads, exports, credits, and status checks through clear, mapped commands. - Error handling and workflow guidance provided for a seamless editing experience.
Metadata
Slug generator-from-audio
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Generator From Audio?

generate audio files into audio-driven videos with this skill. Works with MP3, WAV, AAC, M4A files up to 200MB. podcasters, content creators, marketers use i... It is an AI Agent Skill for Claude Code / OpenClaw, with 43 downloads so far.

How do I install Generator From Audio?

Run "/install generator-from-audio" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Generator From Audio free?

Yes, Generator From Audio is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Generator From Audio support?

Generator From Audio is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Generator From Audio?

It is built and maintained by vcarolxhberger (@vcarolxhberger); the current version is v1.0.0.

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