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 agentmods add skills/dyoshikawa/rulesync/triage-issuesnpx skills add dyoshikawa/rulesync --skill triage-issuesgit clone --depth 1 https://github.com/dyoshikawa/rulesyncWhat 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 | $0.00026 | $0.00812 |
| Opus 5 | $0.00013 | $0.00406 |
| Sonnet 5 | $0.00005 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
triage-issues 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 2d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Triage Open Issues
Review all open GitHub issues that currently have no labels and apply the most appropriate labels based on their content.
Step 1: List Available Labels
Fetch the full list of labels defined in this repository so the triage stays within the known label set:
gh label list --limit 100
Treat this list as the authoritative vocabulary. Do not invent new labels.
Step 2: Find Unlabeled Open Issues
Fetch all open issues that have no labels attached:
gh issue list --state open --search "no:label" --limit 100 --json number,title,author,url
If the result is empty, report that nothing needs triage and stop.
Step 3: Gather Context per Issue
For each unlabeled issue, read the description and the discussion so the label choice is grounded in the actual content:
gh issue view <issue_number>
gh issue view <issue_number> --comments
Run these in parallel across issues where practical.
Step 4: Decide the Labels
For each issue, pick the labels that best describe it. Typical signals:
bug— something is broken or behaves incorrectly.enhancement— a new feature, new tool/feature support, or a capability request.documentation— docs, README, ordocs/**/*.mdchanges.refactoring— internal restructuring without behavior change.improvement— quality, DX, or polish work that isn't a bug or a new feature.question— the author is asking for clarification or usage help.duplicate— already tracked by another issue (link it in a comment if you apply this).invalid/wontfix— only if the issue itself states this or the content clearly indicates it; otherwise skip.good first issue— small, well-scoped, approachable for newcomers.help wanted— maintainer explicitly wants external contribution; do not apply speculatively.considering— proposals that are worth discussing but not yet accepted.high priority— explicit urgency signals (regression, blocking users, security). Be conservative.security— security-relevant reports or hardening work.codex— specific to the Codex CLI integration.maintainer-scrap— do NOT add this unless the issue body explicitly says so; it's reserved for maintainer-only scratch notes.
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.
- 2d ago First seen · 89 lines · 26 tokens per session scan A f9bb5415d7d1
triage-issues is a skill published in the GitHub repository dyoshikawa/rulesync (1,373 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 812 once invoked, about $0.0001 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.
Other skills, from other repositories
deep-clean
Full-spectrum consolidation of AI agent configuration files. Goes beyond memory-only dream skills: audits and optimizes context files (AGENTS.md/AGENTS.md/GEMINI.md/.cursorrules), rules, skills, and memory. Detects stale references, dead file paths, duplicated rules, stack mismatches, contradictions, vague directives…
turborepo
Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines…
shadcn
Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for…
skill-creator-anthropic
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
skill-creator-openai
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
impeccable
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states.…