app-ai-guardrails
SolidScaffold 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.
Install
Quality Score: 81/100
Skill Content
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
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ci-pipeline-and-gates
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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.
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.