Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation

Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement

5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance

Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.

Comprehensive architecture patterns, methodologies, quality frameworks, and evaluation methods for solution architects. Load when designing system architecture or selecting patterns.

Domain-specific authoritative source databases, search strategies by topic category, and source freshness rules

BDD patterns for acceptance test design - Given-When-Then structure, scenario writing rules, pytest-bdd implementation, anti-patterns, and living documentation

BDD requirements discovery methodology - Example Mapping, Three Amigos, conversational patterns, Given-When-Then translation, and collaborative specification

Bug fix workflow: root cause analysis → user review → regression test + fix via TDD

Canary skill for auto-injection detection

CI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.

Cross-agent collaboration protocols, workflow handoff patterns, and commit message formats for TDD/Mikado/refactoring workflows

Documentation collapse anti-patterns - detection rules, bad examples, and remediation strategies for type-mixing violations

Best practices for command definition files - size targets, declarative template, anti-patterns, and canonical examples based on research evidence

Step-by-step workflow for converting bloated command files to lean declarative definitions

Detects current wave progress for a feature and resumes at the next step. Scans docs/feature/ for artifacts.

Data architecture patterns (warehouse, lake, lakehouse, mesh), ETL/ELT pipelines, streaming architectures, scaling strategies, and schema design patterns

Database comparison catalogs, RDBMS vs NoSQL selection criteria, CAP/ACID/BASE theory, OLTP vs OLAP, and technology-specific characteristics

Rollback procedures, risk assessment, pre/post-deployment validation, and contingency planning. Load when orchestrating deployment or preparing rollback plans. For deployment strategy details (canary, blue-green, rolling), see `cicd-and-deployment` skill.

Designs system architecture with C4 diagrams and technology selection. Use when defining component boundaries, choosing tech stacks, or creating architecture documents.