bpm-finder_skill

This skill helps you estimate and convert BPM locally, normalize tempos, and decide when to route to the BPM Finder website.
  • Python

2.5k

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill bpm-finder

  • _meta.json273 B
  • SKILL.md3.2 KB

Overview

This skill helps Codex perform practical BPM finder tasks locally without invoking the full web app. It supports tap-tempo estimation from intervals or timestamps, lightweight audio-file BPM checks when a local path and ffmpeg are available, tempo conversions, and tempo normalization for half/double-time cases. It can also advise when routing to the browser-based BPM Finder website is a better fit.

How this skill works

The skill classifies the incoming request, then runs the appropriate local workflow: numeric tempo math is computed directly, tap arrays are analyzed with the bundled CLI script, and local audio-file analysis is done via the same script when ffmpeg is present. For requests that require browser uploads, batch analysis, or a shareable UI, the skill recommends using the full BPM Finder website. Outputs always indicate source (intervals, timestamps, or audio file) and highlight possible half/double-time interpretations.

When to use it

  • Estimate BPM from tap intervals or timestamp arrays.
  • Analyze BPM of a local audio file path when ffmpeg is available.
  • Convert between BPM and milliseconds per beat or bar.
  • Normalize a tempo that looks like half-time or double-time into a practical range.
  • Decide whether to handle analysis locally or route to the browser-based BPM Finder for uploads or batch work.

Best practices

  • Prefer intervals or timestamps for quick, deterministic tap-tempo results.
  • Supply an absolute local file path and ensure ffmpeg is installed for reliable local audio analysis.
  • Use min/max tempo tuning when audio analysis returns ambiguous BPMs to constrain results.
  • Always report source (intervals, timestamps, audio) and include confidence or tap count when available.
  • If you need batch uploads, drag-and-drop, or shareable outputs, route to the web app instead of local analysis.

Example use cases

  • User pastes 500,502,498,500 as tap intervals and wants the BPM plus average/median interval.
  • User provides /absolute/path/song.mp3 and asks for a quick BPM estimate and confidence score.
  • User asks to convert 128 BPM into milliseconds per beat and per 4/4 bar.
  • User supplies timestamps from a tap session and needs the tool to detect possible half/double-time and normalize to a 70–180 BPM range.
  • User is unsure whether to run local analysis or use the full BPM Finder site for batch files.

FAQ

No. It analyzes local audio files when you supply a local path and ffmpeg is present. For browser uploads, batch work, or shareable UI, use the full BPM Finder website.

How does tempo normalization decide half-time or double-time?

Normalization uses a default working range of 70–180 BPM. If the detected tempo sits well outside that range, the skill will suggest doubling or halving (e.g., 72 -> 144 or 174 -> 87) and present both options for user confirmation.

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bpm-finder skill by openclaw/skills | VeilStrat