# Energy Calculator

> Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks. Use when this capability is needed.

- Skill: `tomevault-io/energy-calculator` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/energy-calculator`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/energy-calculator/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/energy-calculator

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# Energy Calculator

Calculates per-second RMS (Root Mean Square) energy from audio files. Produces an energy profile that can be used for opening detection, pause detection, or other audio analysis tasks.

## Use Cases

- Calculating audio energy for silence detection
- Preparing data for opening/pause detection
- Analyzing audio volume patterns

## Usage

```bash
python3 /root/.claude/skills/energy-calculator/scripts/calc_energy.py \
    --audio /path/to/audio.wav \
    --output /path/to/energies.json
```

### Parameters

- `--audio`: Path to input WAV file
- `--output`: Path to output JSON file
- `--window-seconds`: Window size for energy calculation (default: 1 second)

### Output Format

```json
{
  "sample_rate": 16000,
  "window_seconds": 1,
  "total_seconds": 600,
  "energies": [123.5, 456.7, 234.2, ...],
  "stats": {
    "min": 45.2,
    "max": 892.3,
    "mean": 234.5,
    "std": 156.7
  }
}
```

## How It Works

1. Load audio file
2. Split into 1-second windows
3. Calculate RMS energy for each window: `sqrt(mean(samples^2))`
4. Output array of energy values

## Dependencies

- Python 3.11+
- numpy

## Example

```bash
# Calculate energy from extracted audio
python3 /root/.claude/skills/energy-calculator/scripts/calc_energy.py \
    --audio audio.wav \
    --output energies.json
```

## Notes

- RMS energy correlates with perceived loudness
- Higher values = louder audio, lower values = quieter/silence
- Output can be used by opening-detector and pause-detector skills

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/benchflow-ai) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-11 -->