Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/stereosam/stereo-vibe-publicWrote 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/commands/stereosam/stereo-vibe-public/golos)<a href="https://agentmods.dev/commands/stereosam/stereo-vibe-public/golos"><img src="https://agentmods.dev/badge/commands/stereosam/stereo-vibe-public/golos/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/commands/stereosam/stereo-vibe-public/golos"><img src="https://agentmods.dev/badge/commands/stereosam/stereo-vibe-public/golos.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 | $0.00020 | $0.00246 |
| Opus 5 | $0.00010 | $0.00123 |
| Sonnet 5 | $0.00004 | $0.00049 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
golos 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 10d 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.
What it actually says
Переключи флаг десктоп-голоса:
- Если файл
<home>\.claude\voice_on.flagсуществует — удали его (ВЫКЛ голос). - Иначе создай его (ВКЛ голос).
Подтверди одной строкой текущее состояние (🔊 ВКЛ / 🔇 ВЫКЛ).
ВАЖНО — пока голос ВКЛ, в конце КАЖДОГО своего ответа добавляй последней строкой:
🔊 <короткая устная выжимка, 1-2 предложения, без кода/markdown/путей>
Stop-хук voice-respond.py берёт текст после 🔊, синтезирует голосом Silero/baya через тёплый
dictate_server (http://127.0.0.1:8765/tts) и проигрывает. Весь код/детали остаются текстом на экране.
Когда голос ВЫКЛ — строку с 🔊 не добавляй.
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.
- 10d ago First seen · 15 lines · 20 tokens per session scan A f6e24b138427
golos is a command published in the GitHub repository stereosam/stereo-vibe-public (1 stars, last pushed 27d ago), licensed MIT. It adds 20 tokens to every session and 246 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
Other commands, from other repositories
tokenless-stats
Show Tokenless compression statistics.
clarify
Reduce spec ambiguity via targeted questions with adaptive auto-invocation (planning is 80% of success).
version
Display current guide and Claude Code versions.
init
Initialize project documentation, preferences, or design tokens.
voice-compliance
Voice/telephony compliance check — invokes voice-ai-reviewer to produce TM-voice-{slug}.md with TCPA, STIR/SHAKEN, state recording-consent, EU AI Act Art. 50, and synth-voice deepfake-law gaps.
crear-skill
Crear, probar y mejorar skills de forma iterativa. Usa cuando el usuario dice "crear skill", "crear habilidad", "build skill", "create a skill", "skill development", "desarrollar skill", "nueva habilidad". Usa el workflow: draft → test → review → improve → repeat con evaluación cuantitativa y qualitative review.