Rulesync is a command-line tool that generates configuration for different AI development tools from a shared set of rules. Developers use it to keep instructions, commands, MCP settings, ignore files, subagents, and skills consistent across coding agents. Catalogue skills support workflows built around Rulesync.
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 dyoshikawa/rulesync --skill batch-review-prs-awaiting-maintainergit clone --depth 1 https://github.com/dyoshikawa/rulesyncWrote 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/dyoshikawa/rulesync/batch-review-prs-awaiting-maintainer)<a href="https://agentmods.dev/skills/dyoshikawa/rulesync/batch-review-prs-awaiting-maintainer"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/batch-review-prs-awaiting-maintainer/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/dyoshikawa/rulesync/batch-review-prs-awaiting-maintainer"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/batch-review-prs-awaiting-maintainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00083 | $0.00861 |
| Opus 5 | $0.00042 | $0.00430 |
| Sonnet 5 | $0.00017 | $0.00172 |
| Haiku 4.5 | $0.00008 | $0.00086 |
Grade A, and why
batch-review-prs-awaiting-maintainer 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 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.
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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Batch Review PRs Awaiting Maintainer
This skill triages a batch of open pull requests end to end. It lists the candidate PRs, reviews each one, and then takes one of two actions per PR depending on whether the review surfaced any merge-blocker-level findings.
A finding is merge-blocker level when it is severe enough that the PR must
not be merged as-is — typically severity high or critical (for example,
correctness bugs, security vulnerabilities, data loss, or broken/failing CI).
Findings of severity mid or low (style nits, minor refactors, non-urgent
improvements) are not merge blockers.
Step 1: List Target PRs
Use the prs-awaiting-maintainer skill to list the open pull requests where
the ball is in the maintainer's court — CI is green and the PR is ready to
review, re-review, or merge. Collect their PR numbers as the work list for the
following steps.
If the list is empty, report that there is nothing to triage and stop.
Step 2: Review and Resolve Each PR
Process the PRs one at a time. For each PR number target_pr:
2-1. Review
Use the review-pr skill with target_pr. It assigns each finding a
severity (low / mid / high / critical) and also reports the GitHub
Actions workflow status.
2-2. Classify
Decide whether the review produced any merge-blocker-level finding (severity
high or critical, or failing/blocked CI), using the definition above.
2-3a. Has Merge-Blocker Findings → Post Comments
If there is at least one merge-blocker-level finding:
- Use the
post-review-commentsskill withtarget_pr, using the review results from Step 2-1 to leave line-level and overall review comments. - Do not merge this PR. The ball goes back to the author.
2-3b. No Merge-Blocker Findings → Issue-ify and Merge
If there are no merge-blocker-level findings (only mid/low findings, or none
at all):
- If any non-blocking findings remain, capture them for later by invoking the
create-scrap-issueskill with the findings (background context plus the suggested follow-ups), so they are tracked as amaintainer-scrapissue instead of blocking the merge. If there are no findings at all, skip this. - Merge the PR by using the
merge-prskill withtarget_pr.
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 · 84 lines · 83 tokens per session scan A 35a46f741ddb
batch-review-prs-awaiting-maintainer is a skill published in the GitHub repository dyoshikawa/rulesync (1,403 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 861 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 2026-08-30.
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branch-pr
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work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
review-delta
Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.
issue-to-pr-resolver
Implement a GitHub issue end-to-end — create a worktree branch, implement the feature with tests, create a draft PR, then iteratively resolve all CI failures and review comments until the PR is clean. Use when you need to fully implement a GitHub issue from start to merge-ready. Triggers on "implement issue", "resolve…