Эксперт AWS Kinesis. Используй для stream processing, real-time data и Kinesis patterns.

Implements frontend forms and actions in Kirby (contact forms, file uploads, email with attachments, creating pages from frontend). Use when handling user input or building submission flows.

Exposes Kirby content to headless clients using the API, KQL, and JSON representations. Use when building API endpoints, KQL queries, or headless frontends.

Secures Kirby sites with access restriction, user roles, permissions, and protected downloads. Use when implementing login/role-based access, permissions, or file protection.

Simulates live updates between Knack backend and Vercel dashboards. Enables near-real-time synchronization of HTI operational data without constant...

Deploy AI agents as serverless workloads using Knative Serving, enabling automatic scale-to-zero and request-based autoscaling.

Knative serverless platform for Kubernetes. Use when deploying serverless workloads, configuring autoscaling (scale-to-zero), event-driven architectures, traffic management (blue-green, canary), CloudEvents routing, Brokers/Triggers/Sources, or working with Knative Serving/Eventing/Functions. Covers installation, networking (Kourier/Istio/Contour), and troubleshooting.

Build frameworks from scattered insights across all braindumps and notes

Designs and builds knowledge graphs to represent entities, relationships, and semantic connections, with query patterns for Neo4j, RDF, and property graphs.

Patterns for ingesting knowledge into vector databases and RAG systems

Extracts knowledge from Amp threads and updates project docs. Use when asked to document recent work, sync docs after an epic, summarize what changed, or update AGENTS.md from thread history.

Kolmogorov Codex Quest

Kommo CRM API via curl. Use this skill for managing leads, contacts, companies, tasks, and sales pipelines.

Use this Skill when working in the Connect monorepo and needing to extract app code into proper Nx libraries.

Implements event-driven architecture with Watermill pub/sub (RabbitMQ/AMQP/message queue) for go-kratos microservices. Creates publisher/subscriber wrappers, event handlers, worker services with context propagation (request_id, correlation_id), and RabbitMQ/AMQP integration. Use when implementing pub/sub patterns, creating message queues, adding event handlers, building worker services for async processing, or setting up background jobs.

Deploy and operate AI workloads on Kubernetes with GPU scheduling, model serving, and MLOps patterns

Manage manifests, Helm charts, autoscaling, and disruption budgets.

Kubernetes deployment strategies and workload patterns for production-grade applications. Use when deploying to Kubernetes, implementing rollout strategies, or designing cloud-native application architectures.

Expert-level Kubernetes cluster management, deployment strategies, networking, and production operations

Kubernetes deployment patterns with Helm charts. Covers deployments, services, ConfigMaps, Secrets, Dapr sidecar injection, health probes, and resource management.

Deploy and manage Kubernetes applications with Helm charts. Covers K8s manifests, kubectl, Kustomize, RBAC, and container orchestration. Use for container deployments, microservices, and cloud-native applications.

Comprehensive guide to Kubernetes container orchestration, covering workloads, networking, storage, security, and production operations

Production Kubernetes platform patterns covering cluster architecture, security, GitOps, observability, autoscaling, and operational guardrails

kubesearch

Use when finding new AI agent skills, discovering capabilities, installing skills from GitHub, searching skill marketplaces, or expanding what Claude can do - like Neo downloading martial arts in The Matrix

L-Space Skill: The Library of All Libraries

L0 regularization for neural network sparsification and intelligent sampling - used in survey calibration

Calculate construction labor rates with overhead, benefits, and productivity factors. Regional rate databases and crew composition.

Lambda Calculus Skill

Clerk for reserve reduction, trespass, survey errors, and railway takings; use when processing the Land_Reduction_Trespass queue.

Foundational GraphQL patterns covering schema design, queries, mutations, subscriptions, and resolvers. Use when building or consuming GraphQL APIs. This is the entry point for GraphQL development.

Foundational SPARQL patterns covering RDF querying, triple patterns, graph patterns, and semantic web fundamentals. Use when querying RDF data or working with knowledge graphs. This is the entry point for SPARQL development.

AI agent with tools (search, calculator) using LangGraph and AI SDK.

Building LLM agents with LangChain and LangGraph, covering tool-calling model initialization, state management, and observability with LangSmith. Triggers: langchain, langgraph, langsmith, agent-executor, chat-model-tools.

AI agent with retrieval tool for document Q&A using RAG and LangGraph.

Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating question-answering systems over document collections or AI assistants with external knowledge bases.

Complete guide for building agents and workflows in LangConfig. Use when users need help configuring nodes, connecting agents, setting up tools, or designing multi-agent systems within the LangConfig platform.

Automates Langfuse Cloud dashboard interactions using Playwright MCP. Captures screenshots for documentation, extracts metrics for monitoring, navigates trace details for investigation, and handles authentication. Use when documenting workflows, creating compliance screenshots, monitoring dashboard metrics, or investigating traces visually. MUST use Playwright MCP tools (mcp__playwright__*) for browser automation.

Use when creating a new LangGraph graph. Start with a minimal graph and iterate.

Create LangGraph workflows as NestJS applications under apps/langgraph/. Use same webhook pattern as n8n, receive same parameters (taskId, conversationId, userId, provider, model, statusWebhook). Wrap as API agents with request/response transforms. CRITICAL: Status webhook URL must read from environment variables. All endpoints follow A2A protocol.

Core concepts for building LangGraph applications. Use when creating StateGraph workflows, defining nodes and edges, managing state with TypedDict/Pydantic, or understanding basic graph structure. Covers state schemas, reducers, node functions, edge types (normal, conditional), and graph compilation.

Prevent silent failures and catch implementation errors in LangGraph pipelines before runtime.

Human-in-the-loop integration for LangGraph workflows with approval and intervention points

Multi-agent architectures with LangGraph. Use when building systems with multiple collaborating agents, implementing supervisor or swarm patterns, creating hierarchical agent workflows, or designing agent handoff mechanisms. Covers langgraph-supervisor, langgraph-swarm, agent-as-tool patterns, and context engineering for multi-agent systems.

Build production-grade agentic workflows with LangGraph using graph-based orchestration, state machines, human-in-the-loop, and advanced control flow

Expert guidance for LangGraph Python library. Build stateful, multi-actor applications with LLMs using nodes, edges, and state management. Use when working with LangGraph, building agent workflows, state machines, or complex multi-step LLM applications. Requires langgraph, langchain-core packages.

Subgraph composition and modular workflow design for LangGraph

Design and implement multi-agent workflows with LangGraph 0.2+ - state management, supervisor-worker patterns, conditional routing, and fault-tolerant checkpointing

LangGraph skill for building stateful agent graphs, subgraphs, checkpoints, conditional flows, parallel execution, streaming, and multi-agent orchestration.

Hybrid language detection algorithm for Vigil Guard v2.0.0. Use for language-detector Flask API, entity-based hints, Polish PESEL/NIP detection, 3-branch pipeline integration, accuracy troubleshooting, and langdetect integration.