Desenvolvimento

Use this skill during Phase 5 to execute functional tests, record results, log defects, and validate UX conformance. Logs defects to Git Issues when available, otherwise to markdown (or JSON, per config) under .claude/sdlc/defects/. Reports code coverage against the configured threshold. Triggered after build is signed off and before deploy. Also trigger when the user says "run tests", "report cov

Crie, corrija, otimize e depure sites WordPress utilizando uma pilha padrão que inclui Astra, Elementor Pro e ACF. Esta skill é ativada para tarefas de desenvolvimento, otimização, segurança ou SEO de WordPress, ou ao mencionar ferramentas como Elementor ou ACF.

Test code conventions. Modify tests only for genuine spec or architecture changes—never trivialize, skip, or align expected values to a buggy implementation. Avoid implementation branches that depend on specific test data values. Use when writing or modifying test code, or when tests are failing.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

Java coding standards for Spring Boot services: naming, immutability, Optional usage, streams, exceptions, generics, and project layout.

Dispatches one subagent per independent domain to parallelize investigation/fixes. Use when you have 2+ unrelated failures (e.g., separate failing test files, subsystems, bugs) with no shared state or ordering dependencies.

Detect signatures of natural selection using Fst, Tajima's D, iHS, XP-EHH, and other selection statistics. Calculate population differentiation, test for departures from neutrality, and identify selective sweeps with scikit-allel and vcftools. Use when computing selection signatures like Fst or Tajima's D.

Build maximum likelihood phylogenetic trees using IQ-TREE2 and RAxML-NG with expert model selection, branch support assessment, and topology testing. Use when inferring publication-quality ML trees, selecting substitution models, interpreting bootstrap and concordance factor support, or running partitioned phylogenomic analyses.

AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.

AI-native advisory practice for the Broomva ecosystem. Encodes top-firm consulting methodology (Three Horizons, MIT CISR digital maturity, JTBD, Value Proposition Canvas, RICE/ICE/WSJF, NPV + Real Options, QuantumBlack ML lifecycle, Wardley Mapping) as runnable typed primitives. Produces 7 Discovery-grade deliverables in two modes — consultant CLI or autonomous Life Runtime endpoint. Use when: (1)

Design judgment via design-director taste — reads design intent, assesses whether execution serves it, returns opinionated verdict with clear direction. Scales from one element to a whole app. Always judgment, never fixing. Invoke ONLY via /eye — do NOT trigger on 'review the design' or 'how does it look'.