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 post-review-commentsgit 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/post-review-comments)<a href="https://agentmods.dev/skills/dyoshikawa/rulesync/post-review-comments"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/post-review-comments/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/post-review-comments"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/post-review-comments.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 | $0.00026 | $0.00495 |
| Opus 5.5 | $0.00010 | $0.00198 |
| Sonnet 5.5 | $0.00005 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
post-review-comments 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: Understand the PR
Read the PR diff and description to understand:
- What changed and why
- The scope and impact of the changes
Step 2: Prepare Line-Level Comments
Identify specific lines in the diff that deserve feedback — bugs, potential issues, style concerns, suggestions for improvement, or questions about intent.
For each comment, note:
- The file path
- The line number (in the new version of the file)
- Your comment text
Step 3: Prepare an Overall Review Comment
Write a brief overall assessment of the PR. This is a summary-level comment, not a repeat of line-level feedback.
Step 4: Post the Review
Use a single gh api call to submit both line-level comments and the overall comment together as one review:
gh api repos/{owner}/{repo}/pulls/{pr_number}/reviews \
--method POST \
-f event="COMMENT" \
-f body="<overall comment>" \
-f 'comments[]={...}' ...
Each line comment requires: path, line (line number in the diff's new file), and body.
If you have no line-level comments, fall back to:
gh pr review <pr_number> --comment --body "<overall comment>"
Writing Style
Write in English only.
Style guidelines — write like a human teammate, not a bot:
- Use plain paragraphs. Avoid headings (
##), horizontal rules (---), and excessive bullet lists. - Keep it conversational and direct. Say what matters, skip the filler.
- Do not use phrases like "Great work!" or "LGTM!" unless you genuinely mean it and have nothing else to add.
- Be honest. If something looks off, say so clearly but respectfully.
- Short is fine. A two-sentence comment is better than a five-paragraph essay with no substance.
Step 5: Report
Output the PR number, a count of line-level comments posted, and a brief summary of the overall comment.
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 · 70 lines · 26 tokens per session scan A 6287b8be5a7e
post-review-comments is a skill published in the GitHub repository dyoshikawa/rulesync (1,560 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 495 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
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.
autofix-pr
Watch a pull request and fix it from a worktree of its own - CI failures, review feedback from trusted authors and merge conflicts are fixed, pushed to the PR branch and answered on the PR under the user's git and gh identity. Usage - /autofix-pr [ | ] [--once] [--every ] [--no-reply] [--yes] [instructions]…
github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
otto-pr-review-loop
Run Polly and OCR on a PR until all findings settle.
resolve-drive-pr
Drive an open PR through Polly/OCR, validation, and maintainer handoff.
gentle-ai-collab-perfect
Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…