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Found 387 Skills
Shared references and cross-cutting rules used by all Infrahub skills. Contains GraphQL query syntax, .infrahub.yml configuration format, and common rules for git integration, display label caching, and Python environment setup. DO NOT TRIGGER directly — loaded automatically by other Infrahub skills when they need shared references.
Apply when building or debugging a VTEX IO session transform app (vtex.session integration). Covers namespace ownership, input-vs-output fields, transform ordering (DAG), public-as-input vs private-as-read model, cross-namespace propagation, configuration.json contracts, caching inside transforms, and frontend session consumption. Use when designing session-derived state for B2B, pricing, regionalization, or custom storefront context.
Prevent silent decimal mismatch bugs across EVM chains. Covers runtime decimal lookup, chain-aware caching, bridged-token precision drift, and safe normalization for bots, dashboards, and DeFi tools.
Official Rails documentation. Use when asked about any Rails-specific topic including ActiveRecord, routing, controllers, views, mailers, jobs, Action Cable, Action Text, Active Storage, migrations, validations, callbacks, associations, caching, security, or internals.
Enable automatic disposal of Riverpod providers when they have no listeners; keepAlive, onDispose, invalidate, ref.keepAlive. Use when preventing memory leaks, caching only while used, or cleaning up resources when a provider is no longer needed. Use this skill when the user asks about auto-dispose, keepAlive, or when to dispose Riverpod state.
Scans code for performance and scalability issues — N+1 queries, missing indexes, unbounded queries, memory inefficiencies, caching gaps, algorithmic complexity, concurrency bugs, and frontend performance problems. Generates severity-scored findings with copy-pasteable fix prompts. Trigger phrases: "performance audit", "performance check", "N+1 detection", "query optimization", "slow code", "performance review".
Understand Steedos Server (builder6/server) architecture. NestJS 11 + Moleculer 0.14 hybrid backend with Express middleware, Socket.IO real-time, Redis sessions/caching, and ObjectQL data access. Covers module organization, bootstrap sequence, middleware stack, guards, dependency injection, and builder6 package ecosystem (@builder6/core, moleculer, tables, files, rooms, pages, oidc, etc.).
Execute KQL management commands (table management, ingestion, policies, functions, materialized views) against Fabric Eventhouse and KQL Databases via CLI. Use when the user wants to: 1. Create or alter KQL tables, columns, or functions 2. Ingest data into an Eventhouse (inline, from storage, streaming) 3. Configure retention, caching, or partitioning policies 4. Create or manage materialized views and update policies 5. Manage data mappings for ingestion pipelines 6. Deploy KQL schema via scripts Triggers: "create kql table", "kql ingestion", "ingest into eventhouse", "kql function", "materialized view", "kql retention policy", "eventhouse schema", "kql authoring", "create eventhouse table", "kql mapping"
Scaffold and architect custom Frappe apps including app structure, hooks, background jobs, service layers, and production hardening. Use when creating new apps, setting up app architecture, or implementing cross-cutting patterns like caching, logging, and error handling.
GitHub Actions CI/CD for Rust+Node.js hybrid repos. Covers workflow structure, installable composite actions, artifact flow, caching, and dev versioning. Use when: (1) setting up or fixing GitHub Actions workflows, (2) adding CI for a Rust+Node.js project, (3) working with composite actions (setup-workspace, rust-cross-build, compute-version, wait-npm-propagation), (4) debugging CI failures, (5) setting up the cross-platform build matrix. Triggers on "CI", "workflow", "GitHub Actions", "cross-build", "artifact", or work in .github/workflows/.
Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.
When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.