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 diff-analyzegit 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/diff-analyze)<a href="https://agentmods.dev/skills/dyoshikawa/rulesync/diff-analyze"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/diff-analyze/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/diff-analyze"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/diff-analyze.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 | $0.00021 | $0.00221 |
| Opus 5.5 | $0.00008 | $0.00088 |
| Sonnet 5.5 | $0.00004 | $0.00044 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
diff-analyze 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
Diff Analyze
Analyze the differences between the current branch and origin/main, and summarize the current work progress.
Step 1: Refresh Main Branch
Fetch the latest main branch state:
git fetch origin main
Step 2: Inspect the Diff
Get the differences between the current branch and main:
git diff origin/main...HEAD
Step 3: Inspect Commit History
Get the commit history of the current branch since it diverged from main:
git log origin/main..HEAD --oneline
Step 4: Summarize the Work
Based on the diff and commit history, summarize:
- The main purpose of the current changes
- The notable files or areas affected
- The current implementation progress
- Any obvious risks, gaps, or follow-up work
Keep the summary concise and practical.
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 · 48 lines · 21 tokens per session scan A 50fdb5b31fd7
diff-analyze is a skill published in the GitHub repository dyoshikawa/rulesync (1,520 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 221 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.
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 current CI, independent Polly and OCR reviews, preview, 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…
review-delta
Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.