What is pull-request-discipline?

A set of rules for preparing a pull request on GitHub or a merge request on GitLab, which asks for code changes to be reviewed and merged.

Use it when preparing or checking a change before merge. It defines the branch and commit format, required summary and test plan, task checklist, and preflight checks; the user performs the merge.

It makes the proposal clear and keeps the branch, commits, tests, and task status aligned with the project process.

How radif-ru/ai-multi-agent-system configures Claude Code and Codex

Reuse

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.

Copy the file

curl -O https://raw.githubusercontent.com/radif-ru/ai-multi-agent-system/main/.agents/skills/pull-request-discipline/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/radif-ru/ai-multi-agent-system

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/pull-request-discipline/github.svg)](https://agentmods.dev/skills/radif-ru/ai-multi-agent-system/pull-request-discipline)

Your own site

<a href="https://agentmods.dev/skills/radif-ru/ai-multi-agent-system/pull-request-discipline"><img src="https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/pull-request-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/radif-ru/ai-multi-agent-system/pull-request-discipline"><img src="https://agentmods.dev/badge/skills/radif-ru/ai-multi-agent-system/pull-request-discipline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 649 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00044	$0.00649
Opus 5.5	$0.00018	$0.00260
Sonnet 5.5	$0.00009	$0.00130
Haiku 4.5	$0.00004	$0.00065

Measured 1mo ago against content hash d0a0cdca278d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pull-request-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 1mo 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.

.agents/skills/pull-request-discipline/SKILL.md · 39 lines

What it actually says

Skill: pull-request-discipline

Правила подготовки PR/MR. Источник истины — _board/process.md §7, §9 и _docs/instructions.md §2.

Когда использовать

Готовишь pull request (GitHub) или merge request (GitLab).
Пользователь попросил создать PR/MR.
Проверяешь готовность ветки к merge.

Алгоритм

Ветка. Одна feature/<NN>-<short-name> на спринт, от main. Не смешивать задачи разных спринтов в одной ветке.
Коммиты — атомарные, по Conventional Commits на русском (см. git-discipline). Ритуал задачи: python3 -m scripts.task start <NN>.<stage>.<task> → код/доки → python3 -m scripts.task done <NN>.<stage>.<task> --note "...".
Перед открытием PR — зелёный bash .agents/skills/git-discipline/scripts/preflight.sh (весь набор гейтов — _board/process.md §7.10; тот же набор прогоняет CI).
Тело PR/MR:
- Summary — что сделано и зачем, 2–5 строк. Ссылка на спринт (_board/sprints/<NN>-*.md).
- Test plan — как проверялось: pytest -q, smoke-test, конкретные тесты на новое поведение.
- DoD — отметить выполненные пункты из файла спринта.
Скоуп PR — один спринт. Не добавлять задачи следующих спринтов (см. process.md §9 п.6).
Merge / push в main — только пользователь по явному запросу (см. process.md §2 п.8 и §9). Агент никогда не делает merge/push самостоятельно.
GitHub vs GitLab:
- GitHub: gh pr create --base main --head feature/<NN>-....
- GitLab: glab mr create --target-branch main --source-branch feature/<NN>-....
- Если CLI нет — дать готовый заголовок и тело для веб-интерфейса.

Чего избегать

Открытия PR при красных pytest/flake8/покрытии.
Смешивания задач разных спринтов в одном PR.
Самостоятельного merge/push в main — это делает только пользователь.
PR без Test plan — reviewer не знает, как проверять.
Больших PR (>300 строк diff) без разбиения на ревьюемые части.

Changes

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.

1mo ago First seen · 39 lines · 44 tokens per session scan A d0a0cdca278d

Subscribe to this mod's changes

pull-request-discipline is a skill published in the GitHub repository radif-ru/ai-multi-agent-system (6 stars, last pushed 21d ago), licensed MIT. It adds 44 tokens to every session and 649 once invoked, about $0.0002 per session on Opus 5.5. 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.

Code review Commits Git and workflow LLM Multi-Agent aiogram local-llm ollama sqlite-vec

guardian

Gatekeeping Git/PR by classifying change essence and recommending granularity, naming, and strategy; the ship recipe also executes PR delivery (create, CI watch, merge, cleanup) with Ask First on merge. Use when PR preparation, commit strategy, or gated PR delivery is needed.

simota/agent-skills · 62 tokens

pr-authoring

Playbook for deployment-aware pull requests — the 11-section format that turns a PR into a reviewable contract; why, decision requested, change map, review order, evidence, verification, risk, rollback. Used for the Define→build handoff and any PR a great-pm-driven project opens.

VandanaAjayDubey111/great-pm · 65 tokens

ai-multi-agent-system: Skill for Claude Code