Skill UI

This advanced guide provides strategies for scaling Sentry in high-traffic, enterprise-level applications handling millions of events daily. It details implementing adaptive sampling based on endpoint criticality, using adaptive error deduplication to manage quotas, and optimizing the SDK for minimal runtime overhead, ensuring robust visibility even under extreme load.

This guide provides enterprise-grade architectural patterns for integrating Sentry into multi-service, microservices environments. It covers centralized configuration modules, standardized project topologies (e.g., one project per service), distributed tracing setup, and robust error handling middleware for Node.js, Express, and Python/FastAPI. Ideal for organizations planning large-scale Sentry rollouts or managing complex service ecosystems.

A comprehensive guide to production-ready error tracking using Sentry SDK in TypeScript and Python. Learn how to implement structured error context via scopes, manage user journeys with breadcrumbs, filter out noise and PII using beforeSend/beforeBreadcrumb hooks, and use custom fingerprinting for accurate issue grouping. Essential for robust observability.

This specialized skill guides users in formatting and structuring content to maximize its eligibility for featured snippets and rich results across Search Engine Results Pages (SERP). It focuses on best practices for Q&A format, list generation, and comparative tables, ensuring content is highly concise, direct, and easily digestible by search algorithms.

Orchestrates Serpapi searches through Composio's Rube MCP by discovering current tool schemas, validating the connection, and executing schema-compliant calls with session reuse and explicit memory placeholders to keep automation workflows reliable.

Guides automation of Serpdog tasks via Composio’s Rube MCP toolkit, covering connection setup, tooling discovery, schema checks, session reuse, and execution best practices for reliable workflows.

Automates Serply workflows by orchestrating Composio’s Serply toolkit through Rube MCP, emphasizing tool discovery, connection checks, schema-compliant execution, and session reuse for reliable operations.

Automates sklearn pipeline builder tasks within ML training, activating on relevant triggers to guide data prep, model training, hyperparameter tuning, and experiment tracking with production-ready code and standards validation.

Automates SLA monitor setup within enterprise workflows, delivering step-by-step guidance, best practices, code/config snippets, and validation to align monitoring, compliance, and integration standards.

Provides a comprehensive guide and framework for building robust, production-grade Slack applications. Utilizes the recommended Bolt framework to handle authentication, event routing, and request verification across Python, JavaScript, and Java. Covers advanced topics like interactive UI design using Block Kit, implementing slash commands, managing OAuth flows, and integrating with Workflow Builder. Ideal for developers building sophisticated, enterprise-level team communication tools.

Automated assistant for SOC2 compliance checks that guides security teams through best practices, code/configuration generation, and validation within advanced enterprise frameworks.

SAELens provides a framework for training and analyzing Sparse Autoencoders (SAEs). SAEs decompose the dense, often polysemantic activations of large language models into sparse, monosemantic features. Use this when you need to discover the discrete, interpretable concepts a model has learned, study feature superposition, or analyze specific safety-relevant behaviors (like bias or deception) within deep neural networks.