Setup Monitoring (Grade A)Claude AI için güvenlik test edilmiş geliştirme yeteneği. Grade A. Hizmete metrics, logger, uyarı gibi monitöring (monitörleme) ayarlamanıza yardımcı olan bir rehberdir. Kullanım durumuysa kullanıcıya monitöring kurulumu veya uyarı ekleme için sorulur.

Why You Should Use This?

Individual users gain 30%+ token savings, avoid repeating standards, and receive security guardrails plus instant scaffolding. Teams get consistent AI behavior, day‑one onboarding, codified patterns, and compounded cost savings. Organizations benefit from always‑on compliance, uniform standards across many projects, central governance, and measurable ROI.

Asked by Umar Farooq · Apr 24, 2026

What You Can Customize?

You can customize project identity (name, description, repo URL), tech stack (languages, frameworks), directory paths, business domain entities, code patterns, testing quality gates, database conventions, internal package scopes, and git/workflow conventions such as branch prefixes and commit formats.

Asked by Freya Solberg · Apr 17, 2026

What it detects?

It detects language indicators (e.g., tsconfig.json, go.mod, requirements.txt), frameworks via dependencies in package.json or requirements.txt, database configurations (ORM configs, .sql files, migrations), testing setups (jest.config, pytest, cypress), infrastructure files (Dockerfile, terraform, serverless.yml), and CI/CD pipelines (.github/workflows, Jenkinsfile).

Asked by Naomi Suzuki · Mar 25, 2026

What's Inside?

Rules (47) enforce coding standards on every AI interaction and are always on. Agents (62) are specialized assistants for complex tasks, invoked on demand. Skills (50) provide step‑by‑step guided workflows, triggered contextually. Commands (37) are lightweight quick actions, invoked on demand. Hooks (12) are automation scripts in the AI loop, event‑driven before/after actions. Templates (9) offer scaffolding for handlers, components, tests, and more.

Asked by Diego Fernández · Mar 10, 2026

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 Sofia Lindqvist · Feb 8, 2026