Skill UI

Master professional Python testing practices using the pytest framework. This guide covers Test-Driven Development (TDD) methodology, advanced features like fixtures (with different scopes), parametrization, assertion techniques, and achieving high code coverage, ensuring robust and maintainable software.

This example demonstrates the structure of a blocked fixture within a testing framework. It serves as a placeholder to illustrate required missing elements, such as a detailed description, and is useful for understanding fixture setup requirements and testing methodology.

This fixture provides a controlled environment for reviewing truncated packages. It is specifically designed for use during skill-reviewer calibration, ensuring that reviewers handle incomplete data sets correctly. Always refer to the comprehensive reference guide before making any decisions.

This skill helps developers and QA engineers transform vague, intermittent, or poorly documented bug reports into a minimal, reproducible, and evidence-backed brief. It guides the user to isolate the exact failure conditions, separate expected outcomes from actual errors, and reduce the issue to the smallest safe failing fixture, ensuring diagnosis occurs before premature repair.

This tool benchmarks the recall of PII detection models, crucial for ensuring privacy compliance before deployment. It uses synthetic fixtures and enforces a recall floor by measuring label-aware exact-span and grapheme recall against predefined gold standards. It is essential for auditing models and preventing critical privacy leaks.

This skill scaffolds a gold-standard annotation project tailored for evaluating clinical NER and de-identification models (OpenMed). It guides users through defining label schemas, writing rigorous guidelines, configuring annotation tools (like BRAT/Label Studio), generating synthetic clinical text, and creating disciplined, non-leaking train/dev/test splits. It ensures that all committed data are synthetic fixtures for reproducible evaluation.

Synthea generates statistically realistic, fully synthetic patient records in multiple standards (FHIR R4, C-CDA, CSV). This tool is essential for developers and researchers needing safe, shareable test data for OpenMed pipelines, CI fixtures, or specialized de-identification leakage gate test sets. It ensures zero risk of exposing real Protected Health Information (PHI).

A specialized downstream skill designed for solving encrypted ZIP/PKZIP challenges, particularly those using the legacy ZipCrypto method in CTF competitions. This workflow utilizes known-plaintext attacks (via tools like bkcrack) to recover internal encryption keys, enabling decryption and extraction without resorting to brute-force password guessing. Use this when a predictable plaintext fixture is available.