Monitoring (Grade A)Security-tested development skill for Claude AI. Grade A. Workflow for implementing comprehensive monitoring and alerting. Use when the user needs to set up or improve service monitoring.

Why You Should Use This?

| Audience | Key Benefits | | -------------------- | ------------------------------------------------------------------------------------------------- | | Individual | 30%+ token savings, stop repeating standards, security guardrails, instant scaffolding | | Teams | Consistent AI behavior, day‑one onboarding, codified patterns, compounding cost savings | | Organizations | Always‑on compliance, same standards across 1,000 projects, central governance, measurable ROI | ---

Asked by Sami Virtanen · Oct 3, 2025

What You Can Customize?

| Section | What It Controls | Example | | ------------- | -------------------------- | ---------------------------------------------- | | project | Project identity | Name, description, repo URL | | techStack | Language, framework, tools | TypeScript + Express or Python + FastAPI | | paths | Directory structure | Where handlers, services, and common code live | | domain | Business entities | Order, Product, Customer + lifecycle states | | patterns | Code patterns | 7‑step handler flow, error handling strategy | | testing | Quality gates | 90% coverage, test/lint/type‑check commands | | database | DB conventions | Soft delete field, timestamp columns, naming | | packages | Internal packages | @your‑org scope, registry URL | | conventions | Git and workflow | Branch prefixes, commit format, PR templates | ---

Asked by Nils Johansson · Sep 5, 2025

What it detects?

| Category | Signals | | ------------------ | ------------------------------------------------------------------------------------------ | | Language | tsconfig.json, go.mod, Cargo.toml, requirements.txt, pom.xml, file extensions | | Framework | Dependencies in package.json / requirements.txt (React, Express, Django, Spring, etc.) | | Database | ORM configs (prisma/, sequelize, typeorm), .sql files, migration folders | | Testing | jest.config., vitest, pytest, cypress/, playwright.config. | | Infrastructure | Dockerfile, terraform/, cdk.json, serverless.yml, cloud SDK deps | | CI/CD | .github/workflows/, .gitlab-ci.yml, Jenkinsfile | ---

Asked by Gunnar Eriksson · Sep 3, 2025

What's Inside?

| Layer | Count | What It Does | How It's Triggered | | ------------- | ----- | ------------------------------------------------- | ----------------------------------- | | Rules | 47 | Enforces coding standards on every AI interaction | Automatically — always on | | Agents | 62 | Specialized assistants for complex tasks | On demand — /agent-name | | Skills | 50 | Step‑by‑step guided workflows with checklists | Contextually — when patterns match | | Commands | 37 | Lightweight, token‑efficient quick actions | On demand — /command | | Hooks | 12 | Automation scripts in the AI loop | Event‑driven — before/after actions | | Templates | 9 | Scaffolding for handlers, components, tests, etc. | Referenced by skills and agents | ---

Asked by Idris Suleiman · Aug 24, 2025

How It Works?

Layer 1 — Pre-Processing: Hooks inject project context and block dangerous commands before your prompt reaches the AI. Layer 2 — Rules Engine: 47 always‑on rules enforce token efficiency, security, architecture, code standards, database conventions, and testing thresholds. Layer 3 — Specialized Processing: The right component activates — an agent, skill, or command — based on your prompt. Layer 4 — Post-Processing: Hooks validate output, auto‑format, scan for secrets, and verify coverage.

Asked by Grace Okafor · Jul 8, 2025