Skill UI

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

Guides creation of competitor comparison or alternative landing pages for SEO and sales enablement, detailing honesty-first messaging, multiple page formats, and centralized competitor data so evaluators can choose confidently.

Scans component namespaces to detect duplicated domain logic across services, then suggests consolidation paths or shared services to improve maintainability and clarity.

Analyzes namespaces to spot root-level orphaned classes, highlights hierarchy violations, and produces flattening or refactoring plans that keep components at leaf-level directories.

Guides chaos engineering experiments by defining objectives, choosing tools such as Chaos Mesh, Gremlin, Toxiproxy, or AWS FIS, injecting failures, monitoring metrics, and recommending fixes to harden services and APIs.

Automates Istio and Linkerd configuration for microservices, generating production-ready manifests and setup code tailored to your infrastructure, emphasizing security, observability, and traffic management best practices.

Connect Claude to Gmail, Slack, GitHub, Notion and 1000+ services so it can send emails, create issues, post messages, and update databases instead of just drafting instructions.

Connect Claude to 1000+ services via the Composio Tool Router so you can actually send emails, file issues, post messages, or update docs and data directly from chat instead of just generating instructions.

Addresses the critical challenge of managing extremely long conversation histories (millions of tokens) in advanced AI agents, such as coding assistants. This technique moves beyond simple token minimization by implementing structured compression strategies (like Anchored Iterative Summarization) to prevent the loss of critical technical details—such as file paths, decisions, and error messages—ensuring the agent maintains functional context across complex, multi-step tasks. It emphasizes optimizing for 'tokens-per-task' rather than just tokens-per-request.

A comprehensive guide to understanding the complete state (context) available to Large Language Models during inference. Covers core components like System Prompts, Tool Definitions, Message History, and Retrieval Augmented Generation (RAG). Learning to engineer context is crucial for building robust, efficient, and reliable AI agent systems by managing the attention budget and ensuring high-signal information delivery.

Framework for improving existing marketing copy through seven sequential sweeps that check clarity, voice, benefits, evidence, specificity, and more while preserving the original message and brand tone.

This tool integrates advanced AI capabilities into the entire Git lifecycle within the IDE. It assists developers by automatically generating standardized commit messages from staged diffs, providing deep code review using the @Git context (checking for vulnerabilities, missing handling), and offering systematic guidance for resolving complex merge conflicts. It streamlines version control and elevates code quality.