Borrowing it
Nothing to install: this file belongs to radif-ru/ai-multi-agent-system. 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/radif-ru/ai-multi-agent-system/main/.agents/skills/async-discipline/SKILL.mdgit clone --depth 1 https://github.com/radif-ru/ai-multi-agent-systemWrote 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/radif-ru/ai-multi-agent-system/async-discipline)<a href="https://agentmods.dev/skills/radif-ru/ai-multi-agent-system/async-discipline"><img src="https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/async-discipline/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/radif-ru/ai-multi-agent-system/async-discipline"><img src="https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/async-discipline.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 | $0.00038 | $0.00472 |
| Opus 5 | $0.00019 | $0.00236 |
| Sonnet 5 | $0.00008 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
async-discipline scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- `requests.get(...)`, `time.sleep(...)`, `open(...).read()` в hot path event loop'а. What it actually says
Skill: async-discipline
Правила работы с асинхронностью. Источник истины — _docs/instructions.md §4.
Когда использовать
- Пишешь handler, tool, сервис или агентный цикл, где есть I/O (HTTP, файлы, Telegram API,
sqlite-vec, Ollama). - Интегрируешь синхронную библиотеку (
sqlite3,ddgs). - Создаёшь клиент внешнего сервиса.
Алгоритм
- Любой I/O — только через
await. В hot path не должно быть блокирующих вызовов. - Не используй
requests,time.sleep, блокирующие SDK. Разрешено:httpx.AsyncClient,ollama.AsyncClient,aiofiles(если нужно). - Синхронную библиотеку оборачивай в
asyncio.to_thread(...)(например,sqlite3,ddgs). - Не создавай новый event loop внутри handlers/tools — всё работает в loop'е, запущенном aiogram.
- Общие клиенты (HTTP, Ollama, SQLite-соединение) создавай один раз на приложение и закрывай при shutdown. В
__init__tool'а — никаких сетевых вызовов, только сохранение зависимостей. - Метод
runу tool — всегдаasync, даже если работа синхронная (единый контракт).
Пример
Синхронный поиск через ddgs внутри async-tool:
results = await asyncio.to_thread(lambda: DDGS().text(query, max_results=top_k))
Чего избегать
requests.get(...),time.sleep(...),open(...).read()в hot path event loop'а.asyncio.run(...)/new_event_loop()внутри handlers и tools.- Создания нового HTTP/Ollama-клиента на каждый запрос вместо переиспользования общего.
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 · 38 lines · 38 tokens per session scan A 17d24da53095
async-discipline is a skill published in the GitHub repository radif-ru/ai-multi-agent-system (6 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 472 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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