489 skills (repositories by github) · sorted by popularity
Review AI prompts for harmful output risks, bias, privacy concerns, security weaknesses, and clarity. Receive an assessment, a revised prompt, and suggested tests with explanations of the principles behind each improvement.
Improve code through repeated experiments against a measurable target, such as execution time or memory use. After defining scope and constraints, the agent tests changes, keeps improvements, reverts unsuccessful attempts, and logs results.
Ask plain-language questions about AWS resources, settings, and costs, and receive readable tables using read-only AWS CLI commands. Inspect services and filter results by region, state, or tags without creating, changing, or deleting resources.
Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
Diagnose Arch Linux problems by reviewing recent updates, service logs, and packages. Get a step-by-step investigation plan, ready-to-copy repair commands, verification steps, and guidance for rollback or cleanup.
Design, refine, or review web and iOS interfaces using the product’s existing components and visual style. Consult relevant screen examples when useful, then inspect the result for layout problems, inaccessible controls, and broken interactions.
Create and manage Arize datasets for evaluation and experiments using the ax CLI. Import records from files, append examples, inspect dataset versions, and export a chosen version for offline analysis, with checks for field consistency and export completeness.
Find and evaluate a small, compatible set of AI Agent Skills for a multi-step goal. Check existing capabilities, compare candidates for fit and safety, identify overlaps, and prepare recommendations with installation subject to user approval.
Check security audit findings against code evidence and trace how untrusted input moves through a system. Guide a second review, document verification gaps, and assess draft reports against a minimum quality score before delivery.
Review AWS infrastructure code and deployed resources against the six Well-Architected pillars. Produce risk-ranked findings, remediation examples, and an architecture diagram, then create GitHub issues for tracking improvements after user confirmation.
Manage Azure DevOps projects, repositories, pull requests, pipelines, and work items through command-line tools. The skill guides authentication, resource operations, and automation scripts, with references for builds, permissions, packages, and common errors.
Manage Azure Container Registry, a service for storing container images, with Azure CLI. Build images in the cloud, copy them between registries, clean up stored artifacts, and configure authentication and network access.
Compare C# Web API source code with its TypeScript or JavaScript clients to find mismatched data fields, required inputs, and response handling. Receive an audit report showing client impact, severity, and confidence in each match.
Coordinate a small AI development team with planning, implementation, and optional independent testing roles. Adapt the process to the work’s complexity, prepare pull requests, and preserve decisions and next steps so later sessions can continue.
Set up a Python project with AWS CDK, a toolkit for defining cloud infrastructure in code. Follow guidance on prerequisites, AWS credentials, virtual environments, dependencies, template generation, deployment preparation, and reviewing changes before deployment.
Design an AI agent around its requirements, or audit an existing agent for architectural problems. Deliver justified decisions, verification plans, and a PDF report with a diagram, covering budgets, permissions, stopping rules, and failure handling.
Analyze a codebase to document its technologies, architecture, dependencies, and implementation patterns. Produce a Markdown reference with optional diagrams, code examples, and guidance for adding features consistently with the existing design.
Inspect existing LLM application records in Arize to investigate errors, slow operations, or behavior changes. Export traces, which group related operations, or individual operations and conversation sessions as JSON using the ax command-line tool.
Turn a screen recording of repetitive work into automation scripts. The skill reconstructs the workflow, proposes options suited to installed tools, and helps build and test the chosen approach while preserving human review steps.
Review an iOS app’s code, settings, and submission materials for App Store rejection risks. Receive prioritized findings with supporting evidence, concrete fixes, verification steps, and draft notes to help reviewers test the app.
Create and fix Adobe Illustrator automation scripts using ExtendScript, Adobe’s JavaScript-based scripting language. Automate changes to artwork, text, layers, and artboards, process multiple files, and prepare exports such as PDF, SVG, and PNG.
Analyze AWS infrastructure definitions, deployed resources, usage metrics, and actual costs to identify savings opportunities. Rank recommendations by savings, risk, and effort, then create individual GitHub issues and a coordinating issue after approval.
Build ASP.NET Minimal API endpoints with explicit request and response types, input validation, and standard error responses. Organize related endpoints and add OpenAPI documentation, a structured description of API operations, parameters, and schemas.
Investigate AWS production incidents using reusable CloudWatch log queries and metric calculations. Narrow affected resources, compare alarms with deployment events, and reconstruct a timeline to identify changes that may explain the symptoms.