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 a-tokyo/agent-skills --skill app-ai-guardrailsgit clone --depth 1 https://github.com/a-tokyo/agent-skillsWrote 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/a-tokyo/agent-skills/app-ai-guardrails)<a href="https://agentmods.dev/skills/a-tokyo/agent-skills/app-ai-guardrails"><img src="https://agentmods.dev/badge/skills/a-tokyo/agent-skills/app-ai-guardrails/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/a-tokyo/agent-skills/app-ai-guardrails"><img src="https://agentmods.dev/badge/skills/a-tokyo/agent-skills/app-ai-guardrails.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 | $0.00224 | $0.04146 |
| Opus 5 | $0.00112 | $0.02073 |
| Sonnet 5 | $0.00045 | $0.00829 |
| Haiku 4.5 | $0.00022 | $0.00415 |
Grade A, and why
app-ai-guardrails 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 12d 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
app-ai-guardrails
Scaffold a greenfield app so the full guardrail canon is live in commit #1 and every one of the 7 gates is verified green before that commit exists. The canon is stack-agnostic; each stack's mechanics live in one adapter file. The differentiator is teeth: gates that fail on violations, not report-only tooling. You wire the canon, run every gate green, prove the tree is clean, then commit.
1. Scope
Greenfield only in v1. Six native adapters — Next.js (deep), NestJS, Django, Go, Rust,
Spring Boot — plus a discovery method that maps the canon to any other stack. All six native
adapters have benchmark medians (Spring Boot: sonnet n3, median 89, all gates green);
discovery is unbenchmarked and says so.
Retrofitting the canon onto an existing codebase — or scaffolding a new package inside an
existing monorepo (every mechanism here assumes repo-root ownership: hooks, CI, commit #1,
.claude/ all at root) — is out of scope. If asked, decline politely and say why (an agent under a
"make gates green" mandate inside real code can weaken tests/code to pass; greenfield bounds that
blast radius), and leave value behind: point the user at references/canon/gate-interface.md for
the 7-gate contract they can wire by hand today.
2. The gate contract
Every guardrailed repo exposes the same 7 gate names on its native runner. The names are identical across stacks; only the runner prefix differs.
| Gate | Semantic |
|---|---|
lint |
maximal static-analysis ruleset; zero warnings tolerated |
typecheck |
strict type pass, check-only — not the build |
test |
unit tests, fast (e2e excluded) |
coverage |
enforce thresholds and exit non-zero under floor — not report |
build |
produce the artifact |
e2e |
in-process/API end-to-end against the real app |
audit |
fail closed on advisories ≥ moderate |
Runner prefix per stack: Next/Nest npm run <gate> · Django uv run poe <gate> ·
Go just <gate> · Rust cargo <gate> · Spring Boot ./gradlew <gate>. format is a
reserved auxiliary task, never an
8th gate (enforced via hooks + the lint gate). Full mechanics, the runner-map rationale,
the zero-warnings flag per linter, and the AGENTS.md contract table: references/canon/gate-interface.md.
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 5.7 KB
- references/adapters/discovery.md 2.5 KB
- references/adapters/django.md 7.9 KB
- references/adapters/go.md 6.3 KB
- references/adapters/nest.md 5.3 KB
- references/adapters/next.md 13 KB
- references/adapters/rust.md 5.7 KB
- references/adapters/springboot.md 19 KB
- references/canon/agent-surface.md 5.9 KB
- references/canon/ci-and-sonar.md 6.6 KB
- references/canon/coverage.md 4.0 KB
- references/canon/gate-interface.md 7.2 KB
- references/canon/supply-chain.md 4.4 KB
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.
- 12d ago First seen · 240 lines · 224 tokens per session scan A 47a71a4d4d9c
app-ai-guardrails is a skill published in the GitHub repository a-tokyo/agent-skills (15 stars, last pushed 1mo ago), licensed MIT. It adds 224 tokens to every session and 4,146 once invoked, about $0.0011 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.
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