Data & AI

Computational methods for statistical inference and optimization

Implements SEO best practices including meta tags, structured data, sitemaps, and search optimization. Use when improving search visibility, adding meta tags, creating sitemaps, or implementing structured data. Triggers on SEO requests, meta tag additions, or search optimization needs.

Environment/config conventions (env vars, defaults, validation, CI/local differences). Use when adding config or diagnosing env-related failures.

Implement SQLite database patterns using the database.py interface with complete SQL isolation. MANDATORY for all database projects. Use when working with databases, data persistence, or SQLite.

Test-Driven Development workflows including red-green-refactor cycle, test-first implementation, outside-in vs inside-out testing, TDD for debugging, and TDD for refactoring. Use when implementing new features, refactoring existing code, using tests to drive design, or debugging with failing tests.

Generate forms using base-joy Connected components and react-hook-form. Use when creating a form, adding form fields, connecting inputs to react-hook-form, implementing validation, or building data entry interfaces.

Generate compelling lead magnet concepts that build lists and convert to paid offers. Use when someone needs top-of-funnel ideas, wants to grow their email list, or asks what should I give away for free. Triggers on: lead magnet ideas for X, how do I build my list, what freebie should I create, top of funnel for X, opt-in ideas, grow my email list. Outputs 3-5 lead magnet concepts with hooks, formats, and clear bridges to the paid offer.

Generate realistic JSON API mock response files with proper data types, nested structures, and configurable record counts. Triggers on "create mock API response", "generate JSON mock data", "fake API data for", "mock endpoint response".

Resets staging database with full schema drop. Use for schema changes or migrations. SINGLE SOURCE OF TRUTH for staging database reset automation.

Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.

Spawn threads on running claude-threads orchestrator

Firebase integration for authentication, Firestore database, and real-time data synchronization. Use when working with Firebase services in the LiveMetro app.

This skill should be used when working on the EduLift Flutter/Dart mobile application for development tasks including implementing new features, fixing bugs, optimizing performance, or maintaining existing code. Use this skill for any coding work on the school transportation management app including UI components, business logic, API integration, state management, and architecture compliance.

Analyze performance-related HTML issues on web pages. Use when users ask to check page performance, audit resource loading, verify lazy loading, check preload hints, or analyze render-blocking resources. Detects missing optimizations, large resources, render-blocking issues, and Core Web Vitals problems.

Creates Claude skills with proper structure and best practices. Use when the user asks to create a new skill, generate a skill, or build a custom Claude capability.

Production monitoring, observability, SLO/SLI management, and incident response.Trigger terms: monitoring, observability, SRE, site reliability, alerting, incident response,SLO, SLI, error budget, Prometheus, Grafana, Datadog, New Relic, ELK stack, logs, metrics,traces, on-call, production monitoring, health checks, uptime, availability, dashboards,post-mortem, incident management, runbook.Completes SDD Stage 8 (Monitoring) with comprehensive production observability:- SLI/SLO definitions and tracking- Monitoring stack setup (Prometheus, Grafana, ELK, Datadog, etc.)- Alert rules and notification channels- Incident response runbooks- Observability dashboards (logs, metrics, traces)- Post-mortem templates and analysis- Health check endpoints- Error budget trackingUse when: user needs production monitoring, observability platform, alerting, SLOs,incident response, or post-deployment health tracking.

Comprehensive PR review for oc (OpenShift CLI). Runs build, tests, and linting, then applies Go style improvements and provides detailed code review feedback.

Reduce LLM API costs without sacrificing quality. Covers prompt caching (Anthropic), local response caching, prompt compression, debouncing triggers, and cost analysis. Use when building LLM-powered features, analyzing API costs, optimizing prompts, or implementing caching strategies.

Manage GitHub Wiki, issues, and repository operations with memory-bank integration, business model validation, and SSH authentication. Automatically loads business context, applies documented lessons learned, and prevents common errors through validation automation.

Comprehensive verification of submodule setup including symlink integrity, template generation, git configuration, and CODITECT framework accessibility.