au-review
Reviews AudioUnit v2/v3 plugin implementations for spec compliance, thread safety, and correctness. Use when the user asks to review an AudioUnit plugin, check…
Explains DSP math concepts to developers who need the theory behind an algorithm. Use whenever the user asks how a signal-processing concept works, wants intuition behind a formula, or hits a math-shaped bug. Trigger on phrases like "how does a Fourier transform work", "explain
$ npx -y skills add kunitoki/sonic-skills --skill audio-math-explainer --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/audio-math-explainerContext preview
The summary Claude sees to decide when to auto-load this skill.
Explains DSP math concepts to developers who need the theory behind an algorithm. Use whenever the user asks how a signal-processing concept works, wants intuition behind a formula, or hits a math-shaped bug. Trigger on phrases like "how does a Fourier transform work", "explain
name: audio-math-explainer description: > Explains DSP math concepts to developers who need the theory behind an algorithm. Use whenever the user asks how a signal-processing concept works, wants intuition behind a formula, or hits a math-shaped bug. Trigger on phrases like "how does a Fourier transform work", "explain z-transforms", "what is convolution", "why does my biquad ring", "what is windowing for", "what causes aliasing", or "how do I convert gain to dB". Also trigger when the user pastes DSP code and asks why it behaves a certain way.
> **The rule:** DSP math is small and composable — each concept builds directly on the last. > Start with what the user needs, then connect it to code they're writing.
| Topic | Core idea | Common "why" | |-------|-----------|--------------| | Fourier transform / DFT / FFT | Decompose signal into frequency components | "Why does my FFT output look wrong?" | | Convolution | Weighted moving average; LTI system response | "How does an IR reverb work?" | | Z-transform | Frequency-domain analysis of discrete systems | "How do filter poles/zeros work?" | | Biquad / IIR filters | Recursive difference equation with feedback | "Why does my filter ring / go unstable?" | | FIR filters | Non-recursive weighted sum | "How do I design a linear-phase filter?" | | Windowing | Reduce spectral leakage in DFT | "Why are FFT edges smeared?" | | Sample rate / Nyquist | Highest representable frequency = sr/2 | "What causes aliasing?" | | Decibels | Log scale for amplitude/power ratios | "How do I convert gain to dB?" |
If the user's question maps to multiple rows, start with the most fundamental one and build up.
For each concept, give exactly these three things in order:
1. **Intuition** — one sentence a musician could understand 2. **Math** — the key formula (inline, no walls of derivation) 3. **Code** — one-line pseudocode or a real function call from common audio libraries
Keep each anchor to 1–3 lines. Cut anything that doesn't directly answer the question.
After the three anchors:
| Math concept | Where it shows up in code | |--------------|--------------------------| | DFT basis frequencies | `bin_index * sr / N` — each FFT bin | | Convolution sum | FIR tap loop: `y[n] = sum(h[k] * x[n-k])` | | Z-plane pole radius | IIR feedback coefficients `a1`, `a2` | | Nyquist limit | `if (freq > sampleRate / 2) clamp(...)` | | Window function | Multiply `x[n] *= window[n]` before FFT | | dB conversion | `gain_db = 20 * log10(amplitude)` |
### [Concept name] **Intuition:** [one sentence] **Math:** `[formula]` **Code:** `[one-liner]` **In your code:** [where this appears and what it means for their specific question]
> See `references/dsp-math-reference.md` for full formula tables, gotchas, and property lists.
Precision audio-engineering skills for AI agents. Sonic Skills is a curated pack of Markdown skills for reviewing, debugging, explaining, and implementing audio software.
Repo: kunitoki/sonic-skills
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