Скиллы для вашего ИИ

Build efficient, scalable monorepos that enable code sharing, consistent tooling, and atomic changes across multiple packages and applications.

Curated upstream guidance for Monte Carlo Analyze Root Cause; use when the workflow matches the user goal.

Curated upstream guidance for Monte Carlo Asset Health; use when the workflow matches the user goal.

Route data-related requests to the right Monte Carlo skill or workflow. USE WHEN alerts, incidents, data broken, stale, coverage gaps, data quality, or any ambiguous data observability request.

Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.

Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.

Diagnoses pipeline performance issues -- slow jobs, expensive queries, latency trends -- using Monte Carlo's cross-platform observability. Uses a tiered investigation approach: discover problems, bridge to affected tables, then drill into root causes.

Surfaces Monte Carlo data observability context (table health, alerts, lineage, blast radius) before SQL/dbt edits.

Expert guide for pushing metadata, lineage, and query logs to Monte Carlo from any data warehouse.

Investigate and remediate data quality alerts using Monte Carlo MCP tools. Runs root cause analysis, assesses blast radius, discovers available tools (MCP/CLI/API), proposes and executes fixes, or escalates with full context when uncertain.

Analyze a warehouse for stale, unused, or redundant tables via the analyze_storage_costs MCP tool. Classifies waste patterns and table categories, computes safety tiers, and handles category drill-downs and lineage follow-ups.

Generates SQL validation notebooks for dbt PR changes with before/after comparison queries.

Monthly closing register: period dates, cash/bank/party/inventory/TDS reconciliation flags, profit, receivables, payables, working capital, open adjustments and reviewer. Use for period close.

This skill guides you through creating custom external web service APIs for Moodle LMS, following Moodle's external API framework and coding standards.

Anti-over-engineering guardrail that activates when an AI coding agent expands scope, adds abstractions, or changes files the user did not request.

Generate images and videos with MuAPI's schema-driven asynchronous media API while protecting keys, polling, and output downloads.

Conselho de especialistas — consulta multiplos agentes do ecossistema em paralelo para analise multi-perspectiva de qualquer topico. Ativa personas, especialistas e agentes tecnicos simultaneamente, cada um pela sua otica unica, e consolida em sintese decisoria final.

Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.

Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.

This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.

Route tasks to specialized AI agents with anti-duplication, quality gates, and 30-minute heartbeat monitoring

Decision framework and patterns for architecting applications across AWS, Azure, and GCP.

Build and deploy the same feature consistently across web, mobile, and desktop platforms using API-first architecture and parallel implementation strategies.

Cross-validate web research and produce an offline-checkable evidence ledger with explicit source diversity, confidence, conflicts, and gaps.

Design secure, multi-tenant LLM hosting platforms with tenant isolation, quotas, billing attribution, noisy-neighbor protection, and per-tenant policy controls.