app-ai-guardrails

Solid

Scaffold a new production application with the full agentic-AI guardrail canon baked in from commit #1: a uniform 7-gate interface (lint, typecheck, test, coverage, build, e2e, audit) on each stack's native runner, strict types, maximal static analysis, coverage thresholds with teeth plus seed tests, pre-commit hooks, hardened CI with optional SonarCloud, supply-chain pinning, and an agent-ready AGENTS.md — every gate verified green before the first commit. Native adapters: Next.js, NestJS, Django, Go, Rust, Spring Boot; a discovery method maps the canon to other stacks. USE FOR: creating or scaffolding a new app, service, or API from scratch; bootstrapping a greenfield repo that AI agents will build in. DO NOT USE FOR: retrofitting an existing codebase or scaffolding a new package into an existing monorepo (both assume repo-root ownership), LLM-safety or content-moderation guardrails, or adding a single tool to an existing project.

AI & Automation 15 stars 1 forks Updated 1 months ago MIT

Install

View on GitHub

Quality Score: 81/100

Stars 20%
40
Recency 20%
75
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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 | |---|---| ...

Details

Author
a-tokyo
Repository
a-tokyo/agent-skills
Created
4 months ago
Last Updated
1 months ago
Language
JavaScript
License
MIT

Integrates with

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

ci-pipeline-and-gates

Enforces a lean GitHub Actions Flutter CI where every gate maps to one named release-blocking contract — pinned runner + subosito/flutter-action@v2 toolchain, dart format --set-exit-if-changed, flutter analyze --fatal-infos, build_runner and drift schema freshness (git diff --exit-code), flutter test --test-randomize-ordering-seed random, static import/banned-string greps that catch what runtime can't, coverage-as-report-never-a-gate with the upward-lie fixed, verify-never-bless goldens (no --update-goldens in CI), and an honest statement of what CI cannot prove (audio, real fonts, on-device behaviour). Use when editing .github/workflows/*.yml, adding or removing a job or step, wiring a codegen/schema/format/analyze/coverage gate, writing a grep-based policy test or gate script under test/policy or tool/, pinning action versions, or claiming CI proves something it can't.

0 Updated 1 months ago
zakariaf
AI & Automation Listed

guardrails

Code quality verification gates wired into the agent lifecycle. Use this skill whenever writing, modifying, reviewing, or debugging code — including new features, bug fixes, refactors, troubleshooting, CI/CD setup, or project bootstrapping. Also use when the user mentions "quality", "testing strategy", "CI pipeline", "guardrails", "debugging", or asks how to improve code reliability. If you're writing code or trying to understand why code isn't working, this skill applies. Do not use for README/prose-only edits, copywriting, or documentation wording changes unless the user asks for code/build/CI verification or the docs change affects generated/runtime output.

2 Updated 1 months ago
adewale
AI & Automation Listed

guardrails-configurator

Interviews you to configure project engineering guardrails (code, architecture, security, testing, git/PR, ops, AI agent behavior) and writes them to a durable project file. Use for greenfield setup, “set our rules”, or refreshing standards. Emits GUARDRAILS_CONFIG. Never invents team policy as fact, never overwrites an existing guardrails file without confirmation, and never starts feature work.

0 Updated 1 months ago
willianbs