dsp-algorithm-guide

An implementation guide for digital signal processing, the computer processing of audio and other signals. It maps common tasks such as filters, reverbs, compressors, pitch shifting, and oscillators to suitable algorithms and verification steps.

In plain words
What is it for?
Use it when implementing audio effects or analysis, including low-pass filters, reverbs, compressors, FFT-based processing, pitch shifters, and anti-aliased oscillators.
Why use it?
It helps choose a reasonable starting algorithm and highlights implementation issues that affect sound quality and correctness. It reduces the risk of selecting an unsuitable approach for the requested effect.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/kunitoki/sonic-skills/dsp-algorithm-guide
Any agent
npx skills add kunitoki/sonic-skills --skill dsp-algorithm-guide
Clone the repo
git clone --depth 1 https://github.com/kunitoki/sonic-skills

Made for: Claude Code, Codex.

Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 853 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00102 $0.00853
Opus 5 $0.00051 $0.00426
Sonnet 5 $0.00020 $0.00171
Haiku 4.5 $0.00010 $0.00085

Measured 2d ago against content hash a1d84107cdca, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dsp-algorithm-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/dsp-algorithm-guide/SKILL.md · 52 lines

How it starts

The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DSP Algorithm Guide

Three steps: pick the right algorithm family, address implementation concerns, then verify correctness.

Step 1 — Identify the algorithm family

User request Algorithm family Recommended starting point
Lowpass / highpass / bandpass / notch Biquad (IIR) Direct Form II transposed
High-quality parametric EQ, resonant filter Biquad cascade or SVF State Variable Filter (SVF)
Shelving / high-shelf / low-shelf Biquad (Audio EQ Cookbook) Peaking EQ or shelf coefficients
Reverb (algorithmic) FDN or Schroeder/Moorer Feedback Delay Network (FDN)
Reverb (convolution / IR) OLA / OLS Overlap-Add with FFT
Compressor / limiter / expander / gate Level detector + gain computer RMS or peak detector + knee curve
Pitch shift / time stretch Phase vocoder or granular Phase vocoder for tonal material
Anti-aliased oscillator BLIT / PolyBLEP / wavetable PolyBLEP for simple waveforms
Spectral processing / analysis STFT pipeline Overlap-Add / Overlap-Save
Waveshaper / saturation Memoryless nonlinearity Soft-clip with oversampling

Step 2 — Implementation concerns

Work through this checklist before writing any DSP code:

  • Stability — confirm the algorithm's stability condition and check it after every coefficient update (e.g., biquad poles inside unit circle).
  • Coefficient precision — use double for coefficient computation; cast to float for the inner loop only if profiling demands it.
  • Denormal protection — use ScopedNoDenormals/FTZ where available, or add explicit state clamps/noise around feedback paths.
  • Latency reporting — if the algorithm introduces latency (e.g., FFT block size), call setLatencySamples() so the host can compensate.
  • Initialisation — clear all delay-line and state memory in prepareToPlay; never assume zero-init across transport loops.
  • Parameter smoothing — ramp filter coefficients or gain values over a block; abrupt changes cause clicks and, for IIR filters, instability.
  • Oversampling — nonlinear stages (waveshapers, saturators) need at least 2x oversampling to suppress alias products.

Read the full file on GitHub · 52 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 52 lines · 102 tokens per session scan A a1d84107cdca

Subscribe to this mod's changes

dsp-algorithm-guide is a skill published in the GitHub repository kunitoki/sonic-skills (18 stars, last pushed 3mo ago), licensed Unlicense. It adds 102 tokens to every session and 853 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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