Topic: tdd
465 skills in this topic.
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nw-data-architecture-patterns
Data architecture patterns (warehouse, lake, lakehouse, mesh), ETL/ELT pipelines, streaming architectures, scaling strategies, and schema design patterns
nWave-ai/nWave 341
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nw-diverger-review-criteria
Review criteria for the nw-diverger-reviewer — validates JTBD rigor, research quality, option diversity, taste application correctness, and recommendation coherence in DIVERGE wave artifacts
nWave-ai/nWave 341
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nw-deliver
Orchestrates the full DELIVER wave end-to-end (roadmap > execute-all > finalize). Use when all prior waves are complete and the feature is ready for implementation.
nWave-ai/nWave 341
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nw-ux-emotional-design
Emotional design and delight patterns for product owners. Load when designing onboarding flows, empty states, first-run experiences, or evaluating the emotional quality of an interface.
nWave-ai/nWave 341
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nw-progressive-refactoring
Progressive L1-L6 refactoring hierarchy, 22 code smell taxonomy, atomic transformations, test code smells, and Fowler refactoring catalog
nWave-ai/nWave 341
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nw-pdr-review-criteria
Evidence quality validation and decision gate criteria for product discovery reviews
nWave-ai/nWave 341
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nw-buddy-command-catalog
All /nw-* commands — what they do, when to use them, which agent they invoke. For the buddy agent to help users pick the right command.
nWave-ai/nWave 341
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nw-production-safety
Agent safety boundaries - input validation, output filtering, scope constraints, and document creation policy
nWave-ai/nWave 341
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nw-pbt-fundamentals
Property-based testing core concepts, property taxonomy, and strategy selection (language-agnostic)
nWave-ai/nWave 341
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nw-sa-critique-dimensions
Architecture quality critique dimensions for peer review. Load when invoking solution-architect-reviewer or performing self-review of architecture documents.
nWave-ai/nWave 341
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nw-pbt-erlang-elixir
Erlang/Elixir property-based testing with PropEr, PropCheck, and StreamData frameworks
nWave-ai/nWave 341
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nw-fp-haskell
Haskell language-specific patterns, GADTs, type classes, and effect systems
nWave-ai/nWave 341
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nw-dor-validation
Definition of Ready checklist criteria, antipattern detection patterns, UAT quality rules, and domain language enforcement for product owner review
nWave-ai/nWave 341
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nw-pbt-dotnet
.NET property-based testing with FsCheck, CsCheck, and fsharp-hedgehog frameworks
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-ux-principles
Core UX principles for product owners. Load when evaluating interface designs, writing acceptance criteria with UX requirements, or reviewing wireframes and mockups.
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-interviewing-techniques
Mom Test questioning toolkit, JTBD analysis, interview conduct, assumption testing framework, and hypothesis design
nWave-ai/nWave 341
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nw-forge
Creates new specialized agents using the 5-phase workflow (ANALYZE > DESIGN > CREATE > VALIDATE > REFINE). Use when building a new AI agent or validating an existing agent specification.
nWave-ai/nWave 341
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nw-ux-emotional-design
Emotional design and delight patterns for product owners. Load when designing onboarding flows, empty states, first-run experiences, or evaluating the emotional quality of an interface.
nWave-ai/nWave 341
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nw-shared-artifact-tracking
Shared artifact registry, common artifact patterns, and integration validation. Load when tracking data that flows across journey steps or validating horizontal coherence.
nWave-ai/nWave 341
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nw-infrastructure-and-observability
Infrastructure as Code patterns (Terraform, Kubernetes), observability design (SLOs, metrics, alerting, dashboards), and pipeline security stages. Load when designing infrastructure, observability, or security scanning.
nWave-ai/nWave 341
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nw-five-whys-methodology
Toyota 5 Whys methodology with multi-causal branching, evidence requirements, and validation techniques
nWave-ai/nWave 341
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nw-discover
Conducts evidence-based product discovery through customer interviews and assumption testing. Use at project start to validate problem-solution fit.
nWave-ai/nWave 341