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 yunbow/ai-dev-os-rules-typescript --skill guideline-checkergit clone --depth 1 https://github.com/yunbow/ai-dev-os-rules-typescriptWrote 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/yunbow/ai-dev-os-rules-typescript/guideline-checker)<a href="https://agentmods.dev/skills/yunbow/ai-dev-os-rules-typescript/guideline-checker"><img src="https://agentmods.dev/badge/skills/yunbow/ai-dev-os-rules-typescript/guideline-checker/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/yunbow/ai-dev-os-rules-typescript/guideline-checker"><img src="https://agentmods.dev/badge/skills/yunbow/ai-dev-os-rules-typescript/guideline-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00027 | $0.00802 |
| Opus 5 | $0.00014 | $0.00401 |
| Sonnet 5 | $0.00005 | $0.00160 |
| Haiku 4.5 | $0.00003 | $0.00080 |
Grade A, and why
guideline-checker 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 9d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Guideline Compliance Checker
A skill that checks whether code changes comply with ai-dev-os guidelines.
When to Execute
- When a review is requested after coding is complete
- When verifying compliance before committing
- When requested with "guideline check", "compliance check", etc.
Execution Steps
1. Get Changed Files
git diff --name-only
If there are no changes, check staged or last commit changes with git diff HEAD~1 --name-only.
2. Identify Relevant Guidelines
Based on the paths of changed files, identify which guidelines to check:
| Changed File Pattern | Guidelines to Check |
|---|---|
*.ts, *.tsx |
common/code.md, common/naming.md |
*/server/*.ts, *-actions.ts |
frameworks/nextjs/api.md, common/security.md, common/error-handling.md |
*/schema/*.ts |
common/validation.md |
*/components/*.tsx |
frameworks/nextjs/ui.md, frameworks/nextjs/form.md |
*/hooks/*.ts |
frameworks/nextjs/state.md |
prisma/schema.prisma |
frameworks/nextjs/database.md, common/naming.md |
app/**/page.tsx, app/**/layout.tsx |
frameworks/nextjs/routing.md |
app/api/** |
frameworks/nextjs/api.md, common/security.md |
.env* |
common/env.md |
*.test.ts, *.spec.ts |
common/testing.md |
3. Check Items by Guideline
common/security.md (Security)
- Are authentication checks (
auth()) performed in Server Actions? - Is input validated with Zod?
- Are there IDOR protections (resource ownership checks)?
- Is sensitive information excluded from logs?
common/code.md (Coding Conventions)
- Is the
anytype not used? (unknownshould be used instead) - Are function arguments and return types explicitly typed?
- Are Union Literals used instead of Enums?
- Are reasons documented in comments when disabling ESLint rules?
common/error-handling.md (Error Handling)
- Are error responses in a unified format (ActionResult, etc.)?
- Are internal errors not directly exposed to users?
- Are appropriate log levels (ERROR/WARN/INFO) used?
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.
- 9d ago First seen · 100 lines · 27 tokens per session scan A 35c79f03a1b6
guideline-checker is a skill published in the GitHub repository yunbow/ai-dev-os-rules-typescript (2 stars, last pushed 4mo ago), licensed MIT. It adds 27 tokens to every session and 802 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 2026-08-31.
Other skills, from other repositories
ai-dev-os-check
Checks code changes against AI Dev OS guidelines and automatically fixes violations. Based on benchmark Test 011: check+fix achieves +9.9 improvement vs report-only (+0.8). Supports git diff (default), branch comparison, and staged changes. Use --dry-run for report-only mode (no fixes applied).
ai-dev-os-scan
Scans ALL source files in the project against AI Dev OS guidelines. Unlike /ai-dev-os-check (which only checks git diff), this performs a full project-wide compliance scan. Use for initial audits, periodic full reviews, or after introducing new guidelines.
ai-dev-os-review
Performs a comprehensive self-review before creating a PR. Combines guideline compliance checking (L3) with design-level review (L2) and philosophical alignment (L1). Unlike /ai-dev-os-check which only checks rules, this also evaluates architecture decisions and code design quality.
ai-dev-os-extract
Extracts rules from the gap between AI-generated code and ideal code. Used after code review to add new rules to AI Dev OS guidelines. A Rule Harvesting approach to rule discovery.
ai-dev-os-evolve
Supports the spiral evolution of AI Dev OS. Analyzes recent AI coding practices (commit history, review records) and generates update proposals for L1 philosophy and L2 principles. Used in monthly retrospectives or quarterly reviews.
spotpatch
A development workflow for React that connects a selected page element to its JSX or TSX source code and gathers context for review.