juce-agent-toolkit

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Create and inspect audio projects in the JUCE Agent Toolkit Harness workspace, including its local starter and optional upstream integration.

AI & Automation 957 stars 79 forks Updated today MIT

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Skill Content

# Instrument maker Read `studio.json` to understand the current controls; `"$STUDIO_TOOLCHAIN/../studio.config.json"` describes their ranges. Run `"$STUDIO_TOOLCHAIN/run.sh" render` to make a new result. Successful artifacts and their measurements are in `out/runs/<id>/`; `out/latest.json` names the current result. A failed run preserves the last success and records the error in the verdict. The browser audition and Python WAV renderer are local DSP previews. The JUCE action compiles a native offline renderer from the workspace CMake project. JUCE toolkit skills also cover creating full DAW plugins; the starter renderer is not a VST3 plugin. Use `"$STUDIO_TOOLCHAIN/../README.md"` for the integration contract and commands. Read the relevant files under `$STUDIO_UPSTREAM` before using an upstream API. Keep controls within their documented ranges, preserve the data needed to reproduce a comparison, and distinguish preview results from native service or hardware output. The viewer supports history and artifact downloads; tell the user which run contains the result, and what was actually measured. ## Make and validate an instrument Start by changing one audible property: waveform, pitch, attack, or brightness. Render the same four-note phrase before and after. Compare peak/RMS levels and listen to both WAV files. For native DSP changes, edit workspace `Source/main.cpp`, run `juce`, and inspect the measured recording. Keep the CMake target and WAV command arguments intact so t...

Details

Author
autonomous-ai
Repository
autonomous-ai/openharness
Created
1 months ago
Last Updated
today
Language
C
License
MIT

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