Topic: claude-code-skills
8,614 skills in this topic.
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nw-test-design-mandates
Four design mandates for acceptance tests - hexagonal boundary enforcement, business language abstraction, user journey completeness, walking skeleton strategy, and pure function extraction
nWave-ai/nWave 341
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nw-canary
Canary skill for auto-injection detection
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-fp-haskell
Haskell language-specific patterns, GADTs, type classes, and effect systems
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-pbt-dotnet
.NET property-based testing with FsCheck, CsCheck, and fsharp-hedgehog frameworks
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-por-review-criteria
Review dimensions and bug patterns for journey artifact reviews
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-pbt-python
Python property-based testing with Hypothesis framework, strategies, and pytest integration
nWave-ai/nWave 341
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nw-sd-framework
4-step system design framework with back-of-envelope estimation, scaling ladder, and common pitfalls
nWave-ai/nWave 341
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nw-par-review-criteria
Quality dimensions and review checklist for devop reviews
nWave-ai/nWave 341
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nw-review-output-format
YAML output format and approval criteria for platform design reviews. Load when generating review feedback.
nWave-ai/nWave 341
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nw-property-based-testing
Property-based testing strategies, mutation testing, shrinking, and combined PBT+mutation workflow for test quality validation
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-pbt-fundamentals
Property-based testing core concepts, property taxonomy, and strategy selection (language-agnostic)
nWave-ai/nWave 341
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nw-sd-case-studies
25 real-world system design case studies condensed from Alex Xu's System Design Interview Vol 1 and 2 - requirements, architecture, deep dive insights, key takeaways
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-security-and-governance
Database security (encryption, access control, injection prevention), data governance (lineage, quality, MDM), and compliance frameworks (GDPR, CCPA, HIPAA)
nWave-ai/nWave 341
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nw-tr-review-criteria
Review dimensions and scoring for root cause analysis quality assessment
nWave-ai/nWave 341
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nw-buddy-ssot-knowledge
Single Source of Truth detection — where truth lives in an nWave repo and how to avoid contradicting it.
nWave-ai/nWave 341
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nw-spike
Runs a timeboxed spike to validate one core assumption before DESIGN. Use after DISCUSS when the feature involves a new mechanism, performance requirement, or external integration.
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-finalize
Archives a completed feature to docs/evolution/, migrates lasting artifacts to permanent directories, and cleans up the temporary workspace. Use after all implementation steps pass and mutation testing completes.
nWave-ai/nWave 341