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.
npx skills add alifanov/ai-garage-launch --skill unit-economicsgit clone --depth 1 https://github.com/alifanov/ai-garage-launchWrote 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/skills/alifanov/ai-garage-launch/unit-economics)<a href="https://agentmods.dev/skills/alifanov/ai-garage-launch/unit-economics"><img src="https://agentmods.dev/badge/skills/alifanov/ai-garage-launch/unit-economics/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/skills/alifanov/ai-garage-launch/unit-economics"><img src="https://agentmods.dev/badge/skills/alifanov/ai-garage-launch/unit-economics.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 | $0.00073 | $0.00519 |
| Opus 5 | $0.00036 | $0.00260 |
| Sonnet 5 | $0.00015 | $0.00104 |
| Haiku 4.5 | $0.00007 | $0.00052 |
Grade A, and why
unit-economics 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 12d 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
Аналитика и юнит-экономика
Без аналитики ты гадаешь. Ставим с первого дня, разбираем после запуска трафика.
Воронка продукта
visitors ──► users ──► buyers
(зашли) (регались) (заплатили)
Задача — найти где именно проседает и работать над этим местом. Не над всем сразу.
Ключевые метрики
| Метрика | Формула | Ориентир |
|---|---|---|
| CAC — стоимость привлечения | потрачено на канал / число клиентов | чем ниже, тем лучше |
| LTV — ценность клиента | средний чек × срок жизни клиента | > CAC |
| LTV/CAC — главный коэффициент | LTV / CAC | ≥ 3 здорово; < 1 убыток |
| Retention | вернувшиеся / когорта | растёт или выходит на плато |
Retention подробнее
- DAU / WAU / MAU — активные за день/неделю/месяц.
- Когорты — группируем по дате регистрации, смотрим кто возвращается.
- Retention curve — доля активных на день N. Плоское плато = продукт «прилип».
UTM
Размечай все внешние ссылки: utm_source, utm_medium, utm_campaign. Тогда видно, какой источник реально приносит конверсии, а не просто клики.
Инструменты
- Plausible — трафик, источники, цели, страны/устройства. Лёгкий, GDPR-friendly.
- PostHog — продуктовые события, воронки, когорты, retention. Можно оба.
Вывод команды metrics
1–3 конкретных действия: починить узкое место воронки / убить неэффективную UTM-кампанию / усилить работающий источник.
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.
- 12d ago First seen · 46 lines · 73 tokens per session scan A adf3b4f784dc
unit-economics is a skill published in the GitHub repository alifanov/ai-garage-launch (2 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 519 once invoked, about $0.0004 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.
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