Dependency Remediation (Grade A)Habilidade de desenvolvimento testada em segurança para Claude AI. Grau A. Fluxo de trabalho passo a passo para corrigir vulnerabilidades npm/pnpm/yarn e revisar PRs do Dependabot com semver e segurança de CI.

Why You Should Use This?

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 Kalinda Reddy · Nov 12, 2025

What You Can Customize?

Project identity (name, description, repo URL). Tech stack (language, framework, tools). Paths (directory structure for handlers, services, common code). Domain (business entities and lifecycle states). Patterns (code patterns like handler flow, error handling). Testing (quality gates such as coverage thresholds, test/lint/type‑check commands). Database (conventions like soft‑delete fields, timestamps, naming). Packages (internal package scopes and registry URLs). Conventions (Git workflow, branch prefixes, commit format, PR templates).

Asked by Grace Okafor · Nov 4, 2025

What it detects?

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 Anders Lindgren · Oct 15, 2025

What's Inside?

Rules (47): Enforce coding standards on every AI interaction, always on. Agents (62): Specialized assistants for complex tasks, on demand via /agent-name. Skills (50): Step‑by‑step guided workflows with checklists, triggered contextually. Commands (37): Lightweight, token‑efficient quick actions, on demand via /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 Zain Malik · Sep 30, 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 Grzegorz Lewandowski · Sep 22, 2025