generating-sounds-with-ai_skill

Overview

This skill audits TypeScript Web Audio API code for sound synthesis best practices and outputs findings in file:line format. It focuses on context management, envelope usage, sound design, and parameter ranges to ensure reliable, natural, and safe UI sounds. Use it to enforce consistent procedural audio patterns and to catch common pitfalls that affect performance and perceived quality.

How this skill works

The tool scans specified files or user-provided file patterns and checks code against a set of prioritized rules. It detects issues like multiple AudioContext creations, missing context resume checks, improper envelope ramps, poor sound-design choices, and out-of-range parameter values. Results are emitted as file:line entries followed by a compact summary table and suggested parameter translations for user feedback.

When to use it

• Reviewing procedural audio implementations for UI feedback (clicks, confirmations, alerts).
• Auditing code before release to prevent audio performance or clipping problems.
• Validating new sound components or libraries that use the Web Audio API.
• Checking pull requests that add or modify audio playback logic.
• Ensuring sound synthesis follows best practices for mobile and low-power environments.

Best practices

• Reuse a single AudioContext instance and avoid creating one per sound.
• Resume suspended contexts before playback and clean up nodes after sounds end.
• Use exponential ramps with non-zero targets and set initial gain values to avoid glitches.
• Model percussive clicks with filtered noise bursts and use oscillators for tonal sweeps.
• Constrain parameters: click durations 5–15 ms, bandpass 3000–6000 Hz, Q ≈ 2–5, gain ≤ 1.0.

Example use cases

• Scan a codebase to list lines that create new AudioContext instances or forget to resume suspended contexts.
• Find envelopes that use linear ramps or exponential ramps targeting zero and point to exact lines to fix.
• Detect click sounds implemented with oscillators instead of short filtered noise buffers.
• Report filter frequency/Q values and gain settings that exceed recommended ranges for UI sounds.
• Produce a summary table of rule violations and translate user feedback into concrete parameter changes.