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 explain-prgit 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/explain-pr)<a href="https://agentmods.dev/skills/dyoshikawa/rulesync/explain-pr"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/explain-pr/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/explain-pr"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/explain-pr.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 | $0.00015 | $0.00189 |
| Opus 5.5 | $0.00006 | $0.00076 |
| Sonnet 5.5 | $0.00003 | $0.00038 |
| Haiku 4.5 | $0.00002 | $0.00019 |
Grade A, and why
explain-pr 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.
What it actually says
target_pr = the user's request
If target_pr is not provided, use the PR of the current branch.
Step 1: Gather PR Information
Run the following in parallel:
- Get the PR description and metadata:
gh pr view <pr_number> - Get the PR diff:
gh pr diff <pr_number>
Step 2: Analyze and Explain
Based on the PR content, explain the following two aspects:
- Background (Problem/Motivation): What issue or limitation existed before this PR? Why was this change needed?
- Solution: What approach does this PR take to address the problem? Summarize the key changes and design decisions.
Keep the explanation concise and focused. Use the language of the current conversation (follow the user's language).
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 · 27 lines · 15 tokens per session scan A 7bf3ab67b8cc
explain-pr is a skill published in the GitHub repository dyoshikawa/rulesync (1,520 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 189 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
release-notes
Write release notes for a tagged release — a business-impact summary of what changed for the user, plus a thanks section naming every contributor whose commits are in the release. Short by construction.
review-this-branch
Run the nohuman review gate (fresh-session adversarial reviewer + tamper guard) over the current branch or a GitHub pull request, with no server, no database, and no onboarding, and relay the pass/fail checklist.
release
Release gentle-pi through GitHub and npm. Trigger: release, publish, npm publish, GitHub release, version bump.
parallel-pr-review
Use when asked to "review the open PRs", review a batch or stack of pull requests, or run a recurring PR-review pass on a repo — especially with many PRs, stacked branches, conflicts, or security-sensitive changes. Covers grouping, fan-out to review subagents, verdict synthesis, and posting.
ship
Use when code is ready to ship — creates PRs, merges, deploys, and verifies. Handles the full PR-to-production pipeline. Triggers on /ship.