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/automation-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/automation-discipline)<a href="https://agentmods.dev/skills/radif-ru/ai-multi-agent-system/automation-discipline"><img src="https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/automation-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/automation-discipline"><img src="https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/automation-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 | $0.00047 | $0.00695 |
| Opus 5 | $0.00023 | $0.00347 |
| Sonnet 5 | $0.00009 | $0.00139 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
automation-discipline 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 11d 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 — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: automation-discipline
Правило: всё, что детерминировано и повторяемо, автоматизируется инструментом, а не ИИ и не ручной проверкой. Источник истины — AGENTS.md §5 и _docs/instructions.md §13.
Когда использовать
- Замечаешь повторяющуюся ручную или ИИ-сверку (формат, синхронизация конфига/доски, наличие тестов, валидность ссылок).
- Вводишь новое инвариант-правило, которое можно выразить кодом.
- Готовишь скрипт проверки в
scripts/или гейт в.github/workflows/test.yml.
Алгоритм
- Детерминированное — в код. Если проверку/операцию можно выразить правилом (
grep, парсинг, сравнение, прогон тестов), оформи скриптомscripts/<name>.pyи/или гейтом в CI, а не полагайся на внимательность человека или ИИ. - Сигнал к инструменту — повтор. Сделал сверку руками или попросил ИИ дважды → напиши инструмент: он быстрее, дешевле и не «забывает».
- ИИ — для суждений. Архитектура, дизайн, неоднозначные правки — да; механическая сверка, выразимая кодом, — нет.
- Гейт — источник истины. При зелёном гейте не дублируй его ИИ-проверкой; красный гейт чинится, а не маскируется.
- Инструмент — обычный код проекта. Тесты в
tests/, стиль по_docs/instructions.md§3, запускpython -m scripts.<name>, документирование в_docs/instructions.md§13 /_board/process.md.
Действующие гейты
Полный список с командами и моментом запуска — таблица в _board/process.md §7.10 (единый источник; здесь не дублируется). Локально всё сразу — bash .agents/skills/git-discipline/scripts/preflight.sh, в CI — .github/workflows/test.yml.
Автоматизированы не только проверки, но и повторяемые операции: python3 -m scripts.task start|done <NN>.<stage>.<task> — весь ритуал перехода статуса задачи одной командой (_board/process.md §7.3 и §7.9).
Чего избегать
- Ручного или ИИ-контроля там, где уместен скрипт либо CI-гейт.
- Дублирования зелёного гейта ИИ-проверкой.
- Скрипта без теста и без записи в документации.
- «Одноразовых» ручных проверок, которые на деле повторяются из задачи в задачу.
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.
- 11d ago First seen · 36 lines · 47 tokens per session scan A babbcc9b6da4
automation-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 47 tokens to every session and 695 once invoked, about $0.0002 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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