# Digital data burst

Pitched pulses and a quiet texture accompany a digital action.

Source checkpoint: 8dc3dd143f8eb56223e62d40c694689330a94853. Original procedural synthesis by Renaissance Solutions with Codex.
Local review candidate: public distribution and reuse terms have not yet been selected.
Numbered audio, source and presets are preserved unchanged. Listening preferences and use under narration remain pending.

## Make it with your AI assistant

Ask whether your assistant can run Python and return WAV files. Give it this complete folder (or upload this ZIP and ask it to extract the files).
No account keys or Python packages are needed by the recipe. Use the supplied generator to reproduce our takes.
A prompt alone can lead to a different implementation.

Make an original digital data burst for a podcast technology segment.
Use eight short pitched pulses, alternating gently left and right,
above a quieter, gated electronic texture. Keep it compact and dry,
without speech, a melody quotation, reverb, or a final success alarm.
Use a 1.6-second file. Start at 0.08 seconds, space pulses 0.105 seconds
apart, and retain a 0.87-second texture bed.

Use Python's standard library and original synthesis only. Save separate
layers, a 48 kHz / 24-bit stereo master, a mono fold-down, and a 16-bit
stereo WAV preview. Leave 6 dB of sample-peak headroom. Save the source,
a JSON preset with a fixed seed, a manifest, and SHA-256 checksums.

If you can run the code, render and verify the files. Otherwise return
complete code and local commands, and say what remains unexecuted.
Preserve the first take as v001 so a later experiment cannot overwrite it.

## Run locally

Unzip the complete kit and open Terminal in the folder containing this README, effects/, scripts/ and library/.
Python 3.10 or later is required; reference bytes were generated with Python 3.14.3 on macOS.
Run the following commands from that folder. Use a fresh output folder for every attempt; existing takes will not be overwritten.

python3 effects/008-data-burst/src/render.py --preset effects/008-data-burst/presets/v001.json --output tmp/008-data-burst-v001

python3 effects/008-data-burst/src/render.py --preset effects/008-data-burst/presets/v002.json --output tmp/008-data-burst-v002

Open each new preview.wav in an audio player. stereo.wav is the 48 kHz/24-bit master, mono.wav is its mono fold-down, and stems/ contains aligned layers.
Check the retained files and reproduce all WAVs with:

python3 scripts/verify_library.py --reproduce

Byte equality is verified in the recorded runtime; check other runtimes. This command does not judge how a sound feels.

## What we did

1. Place eight tones in a saved pitch pattern.
2. Add a quietly gated noise texture.
3. Save pulses and texture separately.

## Change one thing

Keep v001 unchanged. Copy its preset to v002 and change only
pulse_count from 8 to 5, plus the take label. Preserve the pulse
spacing, pulse duration, pitch pattern, seed, texture duration and
level, pan, file duration, and -6 dBFS peak target. Render both takes.
Check what happens to the bed and the full-file RMS, and leave the
creative preference pending.

Use the supplied source for these parameter names. With newly written code, first identify the equivalent control.
The sequence has five pulses instead of eight, at the same spacing. The background texture is byte-for-byte unchanged.
Both mixes share a sample-peak target; that does not mean they seem equally loud.

## Listen and decide

Do five pulses leave enough room for speech, or make the action feel unfinished?
Put the burst before a calculation explanation. Compare how soon narration can comfortably begin. Compare both takes and the passage without the effect.
Record what you heard, your preference (including neither or undecided), and one next change.
Technical checks passed for the reference files; human listening and use in context remain pending.

## Source identity

The original chapter SHA-256 is a9e8ad83e7a24e1d303aab71e3f021d13beeb10d5a997d360919efcecb835f42.
Each library manifest records source, preset, dependencies and WAV hashes.
The included catalog is the matching single-recipe subset of the pinned Studio catalog.
