Skill UI

A comprehensive, AI-assisted methodology for diagnosing complex software errors in production environments. This skill guides users through the entire debugging lifecycle, from initial triage and gathering observability data (Sentry, DataDog, Jaeger) to generating hypotheses, selecting appropriate debugging strategies (Time-Travel, Chaos Engineering), and performing AI-powered root cause analysis. It culminates in proposing validated fixes and prevention measures.

Automates guidance for implementing error handler middleware in backend services, covering Node.js, Python, Go, microservices, databases, caching, messaging, and architecture best practices with production-ready code and validation.

Provides structured error handling patterns, logging, retry/circuit breaker strategies, and observability workflows across JavaScript, Python, and Go; ideal when designing resilience, retries, aggregated logging, or alerting.

This skill provides guidance on implementing robust error handling strategies to build highly resilient applications. It covers advanced patterns such as circuit breakers, retries, and handling asynchronous errors, ensuring that the application fails gracefully and provides excellent debugging experiences for both developers and end-users.

Automates API Integration error mapping by guiding best practices, generating production-ready code, and validating configurations whenever an error mapping helper workflow is requested.

Auto-activating skill that assists with API Etag handler tasks, guiding REST/GraphQL/OpenAPI/authentication patterns, generating production-ready code, and validating standards.

Provides step-by-step guidance for automating Etermin operations through Composio's Rube MCP, covering tool discovery, connection checks, execution patterns, and schema compliance requirements when using RUBE_* APIs.

Master the complete penetration testing lifecycle, covering all five stages from reconnaissance and scanning to vulnerability analysis using OWASP standards, and advanced exploitation techniques with tools like Metasploit. This skill provides a structured framework for conducting authorized, professional security assessments.

Evaluates large language models across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag) with standardized prompts and metrics, making it easy to benchmark HuggingFace or API models, compare releases, and track training progress.

Provides detailed evaluation of machine learning models using plugin metrics to assess accuracy, precision, recall, F1, and other key indicators, helping users compare models and validate performance before deployment.

Provides comprehensive guidance on building robust evaluation frameworks for complex agent systems. It addresses the inherent challenges of non-determinism and multiple valid paths, enabling systematic performance testing, validating context engineering choices, and measuring continuous improvements across multiple quality dimensions (e.g., factual accuracy, tool efficiency).

Automates Evenium operations through the Rube MCP and Composio toolkit by always discovering current tool schemas, validating Evenium connections, and executing schema-compliant workflows with proper session and pagination handling.