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nWave-ai / nw-speculative-dispatchSpeculative parallel implementation methodology â dispatch N candidate implementations, audit all, score, pick best. Auditability mandate: ALL candidates logged (not just winner).
nWave-ai / nw-spikeRuns a timeboxed PROBE to validate one core assumption, then optionally PROMOTES the probe into a walking skeleton â the first e2e thin slice of the feature, committed and demo-able. Use after DISCUSS when the feature involves a new mechanism, performance requirement, or external integration.
nWave-ai / nw-test-organization-conventionsTest directory structure patterns by architecture style, language conventions, naming rules, and fixture placement. Decision tree for selecting test organization strategy.
nWave-ai / nw-ddd-strategicStrategic DDD â bounded context discovery, context mapping patterns, subdomain classification, ubiquitous language, and organizational alignment
nWave-ai / nw-discussConducts Jobs-to-be-Done analysis, UX journey design, and requirements gathering through interactive discovery
nWave-ai / nw-formal-verification-tlaplusTLA+ 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 / nw-jtbd-opportunity-scoringJTBD opportunity scoring and prioritization - outcome statement format, opportunity algorithm, scoring interpretation, feature prioritization, and opportunity matrix template
nWave-ai / nw-outcome-kpi-frameworkOutcome KPI definition methodology - synthesizes Who Does What By How Much (Gothelf/Seiden), Running Lean (Maurya), and Measure What Matters (Doerr) into a practical framework for measurable outcome KPIs
nWave-ai / nw-sd-patterns-advancedAdvanced distributed patterns - event sourcing, CQRS, saga, stream processing, append-only log, exactly-once delivery, sequencer, double-entry ledger, erasure coding, order book, watermarks
nWave-ai / nw-taste-evaluationDesign taste evaluation framework â DVF primary filter, Apple/Google/Jobs design principles as explicit scoring criteria, weighted decision matrix, and option ranking for the DIVERGE wave
nWave-ai / nw-designDesigns system architecture with C4 diagrams and technology selection. Routes to the right architect based on design scope (system, domain, application, or full stack). Two interaction modes: guide (collaborative Q&A) or propose (architect presents options with trade-offs).
nWave-ai / nw-sc-review-dimensionsReviewer critique dimensions for peer review - implementation bias detection, test quality validation, completeness checks, and priority validation
nWave-ai / nw-buddy-wave-knowledgeWave methodology knowledge for the buddy agent â what each wave does, its inputs and outputs, and how to route questions.
nWave-ai / nw-ddd-eventsourcingEvent Sourcing and CQRS as DDD implementation patterns â when to use, aggregate event streams, projections, snapshots, sagas, upcasting, conflict resolution
nWave-ai / nw-discoverConducts evidence-based product discovery through customer interviews and assumption testing. Use at project start to validate problem-solution fit.
nWave-ai / nw-fp-clojureClojure language-specific patterns, data-first modeling, REPL-driven development, and spec
nWave-ai / nw-fp-haskellHaskell language-specific patterns, GADTs, type classes, and effect systems
nWave-ai / nw-fp-hexagonal-architectureHexagonal architecture patterns with pure core and side-effect shell for functional codebases
nWave-ai / nw-fp-scalaScala 3 language-specific patterns with ZIO, Cats Effect, and opaque types
nWave-ai / nw-fp-usable-designNaming conventions, API ergonomics, and usability patterns for functional code
nWave-ai / nw-jtbd-interviewsJTBD discovery techniques adapted for AI product owner context. Four Forces extraction, job dimension probing, question banks, and anti-patterns for interactive feature discovery conversations.
nWave-ai / nw-mutation-testRuns feature-scoped mutation testing to validate test suite quality. Use after implementation to verify tests catch real bugs (kill rate >= 80%).
nWave-ai / nw-optimize-testsMinimizes test count while preserving coverage. Detects byte-identical pairs, parametrize-inflation, language-guarantee tests, AST-shape tests, stale migration nets. Approval gate before any change.
nWave-ai / nw-quality-frameworkQuality gates - 11 commit readiness gates, build/test protocol, validation checkpoints, and quality metrics
nWave-ai / nw-test-refactoring-catalogDetailed refactoring mechanics with step-by-step procedures, and test code smell catalog with detection patterns and before/after examples
nWave-ai / nw-updateQueues a deferred self-update of nwave-ai. Writes a PendingUpdateFlag that the SessionStart hook replays on the next Claude Code launch, so the current session is not interrupted. Falls back to manual instructions when the package manager cannot be detected.
nWave-ai / nw-fp-algebra-driven-designAlgebra-driven API design with monoids, semigroups, and interpreters via algebraic equations
nWave-ai / nw-fp-principlesCore functional programming thinking patterns and type system foundations, language-agnostic
nWave-ai / nw-jtbd-analysisJTBD methodology for extracting real jobs behind feature requests â job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring
nWave-ai / nw-brainstormingStructured divergent thinking techniques â HMW framing, SCAMPER, Crazy 8s mechanics, and option diversity guarantees. Enforces strict separation of generation and evaluation phases.
