A precision tool for estimating BPM through tap intervals, audio file analysis, and tempo conversion within an AI agent workflow.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bpm-finder
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install bpm-finder using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The BPM Finder skill is a specialized utility designed to handle practical tempo-related tasks directly within your coding environment. As a key component of the Openclaw Skills library, it enables developers to estimate beats per minute from manual tap sequences, convert tempo into millisecond values for production, and analyze local audio files using command-line scripts. It provides a lightweight alternative to full-scale web applications for quick musical calculations.
This skill is particularly effective for users who need immediate feedback on track speed without leaving their IDE. By integrating Openclaw Skills into your development process, you gain access to powerful CLI-based logic that handles tempo normalization and audio processing via standard tools like ffmpeg.
To get started with this addition to your Openclaw Skills, ensure you have Node.js and ffmpeg installed in your environment. Use the following commands to interact with the local scripts:
# Run tap tempo analysis using intervals
node scripts/tap-tempo.js --intervals 500,502,498,500
# Analyze a local audio file
node scripts/tap-tempo.js --audio-file /path/to/track.mp3 --min-tempo 80 --max-tempo 160
The skill generates structured data based on the type of analysis performed. These metrics help in maintaining high accuracy within the Openclaw Skills ecosystem.
| Property | Description | Source |
|---|---|---|
| bpm | The calculated beats per minute | All |
| averageIntervalMs | Mean time between detected beats | Taps |
| confidence | Statistical certainty of the analysis | Audio File |
| analysisWindow | The specific audio segment processed | Audio File |
| beatOffsetSeconds | The time offset of the first detected beat | Audio File |
Loading
An automated research tool for Openclaw Skills that filters and categorizes daily trending papers from Hugging Face into specific research domains.

Heath Ledger is an AI-powered bookkeeping agent that automates transaction categorization and financial statement generation for Mercury and Stripe users.

An autonomous task queue that allows AI agents to outsource complex tasks to other agents or humans via a schema-validated REST API.

A specialized skill for fetching real-time observations and historical statistics directly from WeatherFlow Tempest weather stations.

A secure, local Python-based workflow for merging PDF documents with a focus on data privacy and professional applications.

A sophisticated tool for discovering and comparing product prices across multiple countries and retailers with USD normalization.








































