Browse skills

Automates common Git tasks like branching, merging, committing, and pushing with clear explanations and helpful suggestions.

Automatically configures firewall rules, access controls, and intrusion detection settings based on specified policies.

Helps with performance optimization, optimization as part of building frontend UIs and user experiences workflows.

Automates debugging Lobbi Docs test suite failures by analyzing logs and suggesting root causes.

Refactors Python/Java backend code for improved readability, efficiency, and maintainability using proven design patterns.

Automatically identifies and removes redundant or inefficient code blocks in backend systems for improved performance.

Generates SAP SQLScript code snippets based on natural language prompts, accelerating development and simplifying complex queries.

This skill extracts raw C module code without modifications, enabling direct analysis and potential use in development workflows.

Automates complex tasks using OpenAI agents, optimizing workflows and achieving goals through intelligent automation.

Promptify optimizes your prompts for AI models, boosting response quality and efficiency – a powerful tool for better results.

This skill adds a Tauri system tray icon to your application, providing convenient access to notifications and settings from the taskbar.

Helps with MCP tools, testing as part of orchestrating AI agents and multi-step workflows workflows.

This tool quickly compares two players’ stats and abilities to identify strengths & weaknesses for strategic insights.

The Jira Assistant streamlines your workflow by automating common tasks like issue creation and updates, boosting team productivity and reducing manual effort.

This skill configures linters to automatically check your code for style and potential errors, improving code quality and maintainability.

Analyzes text data to identify inconsistencies, biases, and potential errors like Sherlock Holmes investigates a case.

Provides constructive code review feedback, identifying potential bugs, style issues, and areas for improvement using AI.

Automated code review focusing on security vulnerabilities, performance bottlenecks, and adherence to laurigates' backend style guidelines.

Analyzes scientific papers from Allen Institute for AI's 2014 dataset to extract key findings and relationships.

Analyzes Python code for common errors, style issues, and potential improvements based on RTGS 2017 guidelines.

Analyzes user's skills & experience from documents to identify gaps and suggest targeted learning resources.

Generates comprehensive release checklists tailored to your project's environment and deployment process.

Analyzes text for signs of distress or mental health concerns, offering a quick initial assessment and potential support resources.

Automatically generates custom code hooks to integrate new data sources or functionalities into existing workflows.