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Operate 20+ security tools like Nmap, SQLMap, and Nuclei via structured workflows for authorized penetration testing, vulnerability scanning, and exploitation. Supports information gathering, web exploitation, and password cracking.

This skill enables developers to scaffold, write, and debug enterprise-grade Playwright E2E tests in Java. It enforces the Page Object Model, JUnit 5, and Allure reporting integration. Supports parallel execution, CI/CD pipelines, and thread-safe base classes for production-quality testing. Ideal for Java 17+ environments.

General-purpose browser automation skill using Playwright. Auto-detects local dev servers, writes custom test scripts to /tmp, and executes them with a visible browser. Supports responsive testing, login flows, form submissions, and link checking.

Plotly is a Python library for creating interactive, publication-quality visualizations with over 40 chart types. Ideal for dashboards, exploratory analysis, and presentations requiring hover, zoom, and pan features. Supports both high-level Plotly Express and low-level Graph Objects APIs for flexible data representation.

Execute safe read-only SQL queries against PostgreSQL databases with multi-connection support and defense-in-depth write protection. Ideal for schema exploration, data retrieval, and analysis without risking accidental writes.

Privacy Mask is a CLI utility for detecting and redacting sensitive PII in screenshots and images locally. It supports various detection engines including regex and NER to identify IDs, financial data, and API keys. All processing is offline to ensure data security. Users can run dry-runs before masking. Ideal for debugging and sharing images without exposing private credentials or secrets.

Proofreads and corrects grammar, spelling, punctuation, clarity, and tone while preserving the author's voice. Supports inline text and file processing modes, returning corrected text with a modification log or saving an updated file with 'UPDATED_' prefix.

This skill generates Puppeteer scripts for browser automation, web scraping, and PDF creation. It supports headless Chrome, network interception, wait strategies, and cloud integration for testing. Ideal for automating browser interactions and extracting data efficiently.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

This skill assists developers in creating Pydantic models following a multi-model pattern for clean API contracts. It supports defining Base, Create, Update, Response, and InDB models with camelCase aliases and optional fields. Ideal for Python backend development, ensuring type safety and seamless integration with TypeScript types.

This skill acts as an expert architect to generate complete, production-ready Python project structures. It supports various modern architectures, including FastAPI, Django (full-stack), standalone libraries, and CLI tools. It ensures adherence to best practices, includes dependency management (uv, pip), type hinting, and comprehensive testing skeletons.

Guides an AI agent to give non-judgmental, evidence-informed quit-smoking support: quit planning, craving check-ins, slip debriefs, optional consent-based logging, and escalation to clinicians or quitlines. Not medical care.