Skill UI

This guide provides production-ready, high-quality patterns for integrating with Algolia Search v5. It covers critical architectural aspects such as implementing singleton client management, performing strongly typed searches, robust error handling (including specific API error codes), efficient batch indexing, and handling multi-tenant environments. Use these patterns to refactor existing code and establish reliable coding standards.

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

This comprehensive checklist guides the safe and robust deployment of Cohere API v2 integrations from staging to production. It covers critical steps including API key management, code quality standards, performance tuning, implementing health checks and circuit breakers, and defining full rollback procedures, ensuring mission-critical AI features are reliable for launch.

Provides a comprehensive checklist for deploying Hex data analytics integrations into production. It covers critical operational best practices, including API key management, rate limit handling, error resilience (circuit breakers, exponential backoff), and robust monitoring strategies. This guide ensures that data pipelines are deployed reliably, minimizing downtime and guaranteeing consistent, high-quality data reporting for go-live scenarios.

This harness provides comprehensive, reproducible evaluation pipelines for complex LLM chains and agents (LangChain/LangGraph 1.0). It integrates golden dataset management, LangSmith evaluation, RAGAS metrics, deepeval LLM-as-judge, and structured agent trajectory analysis. Use it when establishing quality benchmarks for new chains, diagnosing performance regressions after model switches, or implementing CI/CD gates to prevent quality drops.

A comprehensive checklist for deploying Foundry-integrated applications to a production environment. It guides users through critical go-live procedures, covering pre-deployment credential management, rigorous code quality checks, setting up robust monitoring and alerting systems, and executing safe rollout and rollback strategies. Essential for ensuring system stability during major releases.

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

A comprehensive guide for authoring high-quality, implementation-ready design systems. It covers foundational elements like color, typography, and spacing, alongside detailed rules for component anatomy, state management, and WCAG 2.2 AA accessibility, ensuring consistency and sophistication.

This tool performs a rigorous, simulated Quality Management System (QMS) audit based on ISO 13485 standards for medical devices. It forces interrogation on critical areas, including Design History Files (DHF), CAPA effectiveness, process validation, risk management (ISO 14971), and post-market surveillance (MDR/FDA QSR). Use it before major audits, commercial launches, or regulatory submissions to identify compliance gaps.

This skill provides specialized internal auditing capabilities for ISO/IEC 42001:2023 AIMS. It helps compliance teams assess gaps across Clauses 4-10, build comprehensive AI risk registers with control mapping, and plan structured internal audits (Clause 9.2). Ideal for pre-certification readiness, scoping internal audit cycles, or integrating AI systems into existing quality/security management systems (ISMS/QMS).

This skill acts as a comprehensive maintenance orchestrator for the brooks-lint plugin repository. It executes a rigorous, sequential subagent pipeline—including authoring, evaluation, QA, trigger auditing, and release management. Use this when adding, editing, or updating skills to ensure all related components (manifests, README, CHANGELOG) are synchronized and adhere to strict quality gates throughout the development lifecycle.

This skill guides users through the complete lifecycle of data quality incident management using Monte Carlo MCP tools. It performs detailed investigation, including root cause analysis and blast radius assessment. It then coordinates various external tools (APIs, CLI) to propose and execute appropriate remediation actions, ensuring all data incidents are resolved with full context.