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/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/commands/alifanov/ai-garage-launch/channel)<a href="https://agentmods.dev/commands/alifanov/ai-garage-launch/channel"><img src="https://agentmods.dev/badge/commands/alifanov/ai-garage-launch/channel/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/alifanov/ai-garage-launch/channel"><img src="https://agentmods.dev/badge/commands/alifanov/ai-garage-launch/channel.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 | $0.00027 | $0.00554 |
| Opus 5 | $0.00014 | $0.00277 |
| Sonnet 5 | $0.00005 | $0.00111 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
channel 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
/garage:channel — один канал трафика
Правило курса: 1 канал, 1 фича. Не распыляйся — выбираем один канал и работаем с ним минимум 2 недели.
Предусловия
Прочитай docs/STATE.md и docs/02-validation.md (нужен подтверждённый донор). Нет — скажи запустить /garage:validate.
Что сделать
Опирайся на скилл traffic-channels (детали по 12 каналам). Ответь на 4 вопроса, затем сверься с матрицей.
4 вопроса:
- Где живёт ЦА? (разработчики → X/Reddit, маркетологи → LinkedIn, массовый B2C → Meta/TikTok, «ищут в гугле» → SEO/Google Ads)
- Они уже ищут решение или ещё нет? (ищут → SEO/Google Ads; нет → соцсети/контент)
- Сколько времени? (2 недели → только платная реклама; 2 месяца → контент; 6 месяцев → SEO)
- Сколько денег? (0 → органика; ~$200 → тест платного канала; >$2000 → масштаб)
Матрица (кому какой канал):
- SEO — разработчики, B2B, нишевые (медленно, но бесплатно и надолго)
- Google Ads — B2B, услуги, «горячие» запросы (высокий интент, дорого за клик)
- Meta Ads — массовый B2C, лайфстайл, визуал (дёшево, но холодная аудитория)
- Reddit — разработчики, нишевые сообщества
- LinkedIn — только B2B
- Product Hunt / Hacker News — разовый всплеск на запуске
Выбери ровно один канал и обоснуй выбор ответами на 4 вопроса.
Артефакт
Запиши в docs/03-channel.md: выбранный канал, обоснование (4 вопроса), первый конкретный шаг для этого канала. Обнови docs/STATE.md: поле Канал, шаг 3 [x].
➡️ Дальше
/garage:spec — собрать продуктовый бриф: ЦА, боль, ОДНА фича, ценностное предложение.
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 · 40 lines · 27 tokens per session scan A bb18415bbac8
channel is a command published in the GitHub repository alifanov/ai-garage-launch (2 stars, last pushed 1mo ago), licensed MIT. It adds 27 tokens to every session and 554 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
maintain
Run automated maintenance — seeker finds bugs from pod logs and raises GitHub issues, fixer picks them up and creates PRs. Can run as a one-shot or scheduled via /schedule.
save
Save current work state for next session. Creates/updates .planning/ files (CHECKPOINT.md, STATE.md, settings.json) so Heimdall resumes with full context. NOT a rewind — saves forward progress. Run before closing a session or at any milestone.
plan-review
Multi-model plan review — AI models independently plan, then converge on the best approach.
review
Multi-model review — AI models independently review any document or general topic, then converge on findings.
code-review
Multi-model code review — AI models independently review code, then converge on findings.
autonomy
Set Heimdall autonomy (1=Guided, 2=Checkpoint, 3=Full Auto) — how much the agent does before asking. Use with a number, +/- to cycle, or no argument to show current.