testing-strategies
Testing strategies including contract testing, snapshot testing, mutation testing, property-based testing, and test organization
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Testing strategies including contract testing, snapshot testing, mutation testing, property-based testing, and test organization
Review Rust dependencies and create/publish cargo-crev package review proofs for the user. Use when the user asks you to review one of their Rust dependencies, audit a crate, or produce a crev proof.
Cleans and interprets raw PHPUnit CI logs into a compact, AI-friendly failure report. Use this skill whenever the user pastes or uploads a PHPUnit log, GitHub Actions test output, CI test results, or asks to interpret/summarize/analyze failing tests. Trigger even if the user says things like "here's my test output", "tests are failing", "can you look at my PHPUnit log", or pastes a block of text that contains PHPUnit output. Always use this skill before attempting to diagnose failures.
Enforces PHPUnit-only testing in this project. Activates when writing tests, reviewing test files, or when any Pest syntax appears (it(), test(), describe(), uses(), expect() chains, beforeEach/afterEach hooks). Scans for and eliminates all Pest references from code, config, and documentation.
Static review rules for authorization, validation, and privilege escalation risks
Orchestrates existing Laravel skills to produce structured PR reviews
Triage rsyslog GitHub issues one issue or cluster at a time, classify stale and current reports, draft or post closure comments, and maintain a local evidence board.
Mirror rsyslog run_checks.yml container validation locally, including the change-gated Ubuntu 26.04 run-ci.sh check run, the clang static analyzer job, late prompt-based audit passes, Cubic review where applicable, service-skip validation, clean-tree rules, and container path caveats.
Standardizes testing and validation for rsyslog using the diag.sh framework.
Audit a local or remote tabular file (CSV/TSV) for common data quality issues — schema, nulls, types, duplicates. Read-only. Use when a dataset needs a quality check before publishing, or a showcase renders wrong (blank cells, garbled numbers, an unsortable date column) and the cause needs isolating.