voice-training-ui: Instructions file for Claude Code

CLAUDE.md

voice-training-ui CLAUDE.md is an instructions file for Claude Code from scratchyone/voice-training-ui. It costs 6,931 tokens per session, scanned A, original, MIT.

A project guide for Voice Garden, an app that tracks voice-feminization practice and provides feedback on recordings. It describes the app’s working style, visual conventions, required tools, and project-specific instructions for Claude.

In plain words
What is it for?
Use it when developing or maintaining Voice Garden, setting up its audio-analysis tools, working with recordings, or following its project and design conventions.
Why use it?
It gives an agent the context needed to make changes that fit the project’s purpose, appearance, and workflow instead of treating it like a generic app.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: reads .claude/ paths.

This is scratchyone/voice-training-ui's own configuration. It tells Claude Code how to work on voice-training-ui itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything voice-training-ui configures →

Reuse

Borrowing it

Nothing to install: this file belongs to scratchyone/voice-training-ui. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/scratchyone/voice-training-ui/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/scratchyone/voice-training-ui

Made for: Claude Code.

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Per session 6,931 This file is loaded in full into every session.
When invoked 6,931 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.06931 $0.06931
Opus 5.5 $0.02772 $0.02772
Sonnet 5.5 $0.01386 $0.01386
Haiku 4.5 $0.00693 $0.00693

Measured 2mo ago against content hash 124a508ab3d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

voice-training-ui CLAUDE.md 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 2mo 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.

CLAUDE.md · 398 lines

How it starts

The opening of the file, as written. The whole thing — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Voice Garden 🌷 — project guide for Claude

A cozy, quantitative voice-feminization training tracker for Rachel. She records herself (usually the Rainbow Passage), tells you what she was practicing, and you analyze it and surface — kindly and specifically — what to work on next.

If she shares a recording or asks how a take went, use the analyze-voice skill (.claude/skills/analyze-voice/SKILL.md). It's the operating manual for the whole workflow; this file is the why and the shape.


Initial setup (first run — read this first if the project is fresh)

This may be a starter copy: the app, the analyze-voice skill, the reusable annotation lib, the shared reference voices (reference.json), and an _example annotation template are all here — but there may be no recordings yet (empty recordings.json). The user adds their own; everything else is structure for you to drive.

Prerequisites (install whatever's missing):

  • ffmpeg — brew install ffmpeg (macOS) / apt-get install ffmpeg (Linux). Required by analyze.py to read mp3/m4a.
  • uv — the Python/dependency manager (https://docs.astral.sh/uv). Use uv, never pip.
  • Node + npm — for the dashboard.

Bootstrap:

uv sync                                   # Python deps (parselmouth, numpy) → .venv
cd dashboard-react && npm install         # dashboard deps
npm run dev                               # → http://localhost:5173

Add the first recording (this drives the whole dashboard):

uv run analyze.py "/path/to/recording.mp3" --label "what they were trying"

Refresh the dashboard. Then author that take's insight by following the analyze-voice skill — copy dashboard-react/src/annotations/entries/_example.tsx to 00N.tsx (matching the new recording's id) and fill in the slots.

Ownership note: this guide and the skill were written for the original user ("Rachel"). Treat "the user" as whoever you're working with now — keep the same warm, compass-not-judge tone and all the conventions below.

Read the full file on GitHub · 398 lines

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. 2mo ago First seen · 398 lines · 6,931 tokens per session scan A 124a508ab3d7

Subscribe to this mod's changes

voice-training-ui CLAUDE.md is an instructions file published in the GitHub repository scratchyone/voice-training-ui (81 stars, last pushed 4mo ago), licensed MIT. It adds 6,931 tokens to every session, about $0.0277 per session on Opus 5.5. 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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