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.
curl -O https://raw.githubusercontent.com/scratchyone/voice-training-ui/main/CLAUDE.mdgit clone --depth 1 https://github.com/scratchyone/voice-training-uiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/scratchyone/voice-training-ui/claude-md)<a href="https://agentmods.dev/instructions/scratchyone/voice-training-ui/claude-md"><img src="https://agentmods.dev/badge/instructions/scratchyone/voice-training-ui/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/scratchyone/voice-training-ui/claude-md"><img src="https://agentmods.dev/badge/instructions/scratchyone/voice-training-ui/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once 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 |
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.
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 byanalyze.pyto 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.
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.
- 2mo ago First seen · 398 lines · 6,931 tokens per session scan A 124a508ab3d7
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.
voice-training-ui CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| voice-training-ui CLAUDE.mdscratchyone/voice-training-ui | Instructions file | 81 | 4mo ago | MIT | A | 6,931 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
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| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |