Results for “coverage”

Guides test-driven development for Spring Boot services using JUnit 5, Mockito, MockMvc, Testcontainers, and JaCoCo to achieve 80%+ coverage.

Write reliable Kotlin tests using Kotest, MockK, coroutine testing, property-based testing, and Kover coverage, following a TDD workflow.

Measures code quality, identifies code smells, and implements quality gates using static analysis and technical debt tracking.

Patch code to bypass checksums, global state, and validation checks that block fuzzer progress, using conditional compilation for C/C++ and Rust.

Guides test-driven development for Django applications using pytest, factory_boy, and Django REST Framework, covering models, views, serializers, and API testing.

Provides comprehensive testing patterns for Perl applications using Test2::V0, Test::More, prove runner, mocking, and coverage analysis with Devel::Cover.

Guides test-driven development for Quarkus 3.x services with JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo coverage enforcement.

Verifies that tests for already-implemented behavior are meaningful by temporarily breaking the production code and confirming the test fails for the expected reason.

Analyzes production code to find gaps in existing tests by reasoning about hypothetical mutations and checking whether tests would catch them.

Set up continuous fuzzing infrastructure for open-source projects using Google's OSS-Fuzz platform, including building and running fuzz harnesses locally and enrolling new projects.

Guides adding characterization tests before modifying or refactoring untested legacy code, using the RGR workflow and strangler fig pattern to reduce risk.

Runs high-performance genomic interval analysis with gtars (databio), a Rust toolkit with Python bindings — the performance-critical backend for the geniml ML library. Use when computing overlaps/jaccard/coverage between BED region sets, indexing intervals with IGD, generating uniwig accumulation/coverage tracks, tokenizing genomic regions for ML, splitting single-cell fragments into pseudobulks, or computing GA4GH refget sequence digests. NOT for training region embeddings (use alterlab-geniml) or non-genomic spatial joins (use alterlab-geopandas). Part of the AlterLab Academic Skills suite.

Write reliable, maintainable Rust tests using unit tests, integration tests, async testing, property-based testing, mocking, and coverage following TDD methodology.

Analyzes test suites across multiple languages and tags each test with standardized traits (positive, negative, critical-path, etc.) for better test categorization and coverage visibility.

Write and run Perl tests using Test2::V0, Test::More, prove, mocking, and coverage analysis with Devel::Cover, following a TDD workflow.

Use when planning how to test any deliverable or system. This skill provides a framework for selecting the right testing approach based on what is being delivered, ensuring comprehensive coverage without unnecessary overhead.

Parse source files to find which ones have no test file referencing their declared types, producing a prioritized worklist of untested files.

Enforces bulk-safety rules, sharing model requirements, CRUD/FLS security, SOQL injection prevention, PNB test coverage, and modern Apex idioms for Salesforce development.

Provides guidance for property-based testing across multiple languages and smart contracts, helping detect patterns where PBT offers stronger coverage than example-based tests.

Reviews code diffs or explicit file sets through independent correctness and QA lenses, producing a severity-ordered verdict for pre-merge audits or review gates.

Refactors production code with test coverage using a TDD workflow that applies approved refactorings one at a time, gates each on passing tests, and commits or reverts accordingly.

Guides test-driven development for Quarkus 3.x services with JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo, targeting 80%+ coverage for event-driven architectures.

Surveys a codebase as a senior advisor and produces prioritized, self-contained implementation plans for other models or agents to execute, without modifying source code.

Publish local changes to GitHub by confirming scope, committing intentionally, pushing the branch, and opening a draft PR through the GitHub app from this plugin, with `gh` used only as a fallback where connector coverage is insufficient.

Write effective unit tests with best practices for any project. Use when writing tests, creating test cases, improving test coverage, increasing confidence before release, or when the user mentions testing. Mutation score / assertion theater → test-mutation.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Runs a multi-phase verification pipeline including build, type-check, lint, tests, security scan, and diff review to ensure code quality before creating a PR.

E2E automation engineer skill for Playwright-driven flow validation, browser interaction coverage, and end-to-end regression checks. Disabled by default for E2E case/spec work; use only when the user explicitly asks for E2E tests or execution.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Write correct, efficient Kusto Query Language queries with coverage of syntax, joins, dynamic types, datetime pitfalls, regex, serialization, memory management, and advanced functions.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Generates test files, creates mocking strategies, analyzes code coverage, designs test architectures, and produces test plans and defect reports across functional, performance, and security testing disciplines.

Use this skill when the user asks about weigh-station bypass services — Drivewyze, PrePass, BestPass, NORPASS, OOIDA toll savings — how they work, eligibility criteria, costs, and how they tie into CSA scores. Reference each provider's coverage area + pricing.

Generate and run Jest tests for Adobe App Builder actions and React Spectrum UI components, including unit, integration, contract, and component tests with mock helpers for Adobe SDKs.