Topic: ai
10,359 skills in this topic.
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nw-platform-engineering-foundations
Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.
nWave-ai/nWave 341
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nw-quality-framework
Quality gates - 11 commit readiness gates, build/test protocol, validation checkpoints, and quality metrics
nWave-ai/nWave 341
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nw-source-verification
Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements
nWave-ai/nWave 341
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nw-investigation-techniques
Evidence collection methods, problem categorization, analysis techniques, and solution design patterns
nWave-ai/nWave 341
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nw-rigor
Selects a quality-vs-token-consumption profile (lean, standard, thorough, exhaustive, custom, inherit) and persists it globally (~/.nwave/global-config.json) or per-project (.nwave/des-config.json). Use when tuning how much rigor wave commands apply.
nWave-ai/nWave 341
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nw-discovery-workflow
4-phase discovery workflow with decision gates, phase transitions, success metrics, and state tracking
nWave-ai/nWave 341
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nw-quality-validation
Type-specific validation checklists, six quality characteristics, and quality gate thresholds for documentation assessment
nWave-ai/nWave 341
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nw-test-refactoring-catalog
Detailed refactoring mechanics with step-by-step procedures, and test code smell catalog with detection patterns and before/after examples
nWave-ai/nWave 341
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nw-sc-review-dimensions
Reviewer critique dimensions for peer review - implementation bias detection, test quality validation, completeness checks, and priority validation
nWave-ai/nWave 341
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nw-opportunity-mapping
Opportunity Solution Trees, opportunity scoring, Lean Canvas, JTBD job mapping, and technique selection guide
nWave-ai/nWave 341
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nw-deployment-strategies
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.
nWave-ai/nWave 341
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nw-operational-safety
Tool safety protocols, adversarial output validation, error recovery patterns, and I/O contracts for research operations
nWave-ai/nWave 341
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nw-discovery-methodology
Question-first approach to understanding user journeys. Load when starting a new journey design or when the discovery phase needs deepening.
nWave-ai/nWave 341
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nw-ab-critique-dimensions
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
nWave-ai/nWave 341
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nw-fp-algebra-driven-design
Algebra-driven API design with monoids, semigroups, and interpreters via algebraic equations
nWave-ai/nWave 341
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nw-test-organization-conventions
Test directory structure patterns by architecture style, language conventions, naming rules, and fixture placement. Decision tree for selecting test organization strategy.
nWave-ai/nWave 341
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nw-pbt-jvm
JVM property-based testing with jqwik, ScalaCheck, and ZIO Test frameworks
nWave-ai/nWave 341
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nw-domain-driven-design
Strategic and tactical DDD patterns, bounded context discovery, context mapping, aggregate design rules, and decision frameworks for when to apply DDD
nWave-ai/nWave 341
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nw-formal-verification-tlaplus
TLA+ and PlusCal for specifying distributed system invariants. Decision heuristics for when formal verification adds value, key patterns, state explosion management, and alternatives comparison.
nWave-ai/nWave 341
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nw-pbt-go
Go property-based testing with rapid and gopter frameworks
nWave-ai/nWave 341
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nw-dr-review-criteria
Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews
nWave-ai/nWave 341
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nw-review-workflow
Detailed review process, v2 validation checklist, and scoring methodology for agent definition reviews
nWave-ai/nWave 341
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nw-bdd-methodology
BDD patterns for acceptance test design - Given-When-Then structure, scenario writing rules, pytest-bdd implementation, anti-patterns, and living documentation
nWave-ai/nWave 341
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nw-po-review-dimensions
Requirements quality critique dimensions for peer review - confirmation bias detection, completeness validation, clarity checks, testability assessment, and priority validation
nWave-ai/nWave 341