# Integrum Global Kailash Vibe Cc Setup 01 Core Sdk > Kailash Core SDK - Foundational Skills - Skill: `tomevault-io/integrum-global-kailash-vibe-cc-setup-01-core-sdk` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/integrum-global-kailash-vibe-cc-setup-01-core-sdk` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/integrum-global-kailash-vibe-cc-setup-01-core-sdk/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/integrum-global-kailash-vibe-cc-setup-01-core-sdk --- # Kailash Core SDK - Foundational Skills Comprehensive guide to Kailash Core SDK fundamentals for workflow automation and integration. ## Features The Core SDK provides the foundational building blocks for creating custom workflows with fine-grained control: - **110+ Workflow Nodes**: Pre-built nodes for AI, API, database, file operations, logic, and more - **WorkflowBuilder API**: String-based workflow construction with type safety - **Dual Runtime Support**: AsyncLocalRuntime (Docker/async) and LocalRuntime (CLI/scripts) - **Advanced Patterns**: Cyclic workflows, conditional execution, error handling - **MCP Integration**: Built-in Model Context Protocol support - **Parameter Passing**: Flexible data flow between nodes - **Zero Configuration**: Auto-detection of runtime context - **Production Ready**: Enterprise features including monitoring, validation, and debugging ## Quick Start ```python from kailash.workflow.builder import WorkflowBuilder from kailash.runtime.local import LocalRuntime workflow = WorkflowBuilder() workflow.add_node("NodeName", "id", {"param": "value"}) # Use context manager for proper resource cleanup (recommended) with LocalRuntime() as runtime: results, run_id = runtime.execute(workflow.build()) ``` ## Reference Documentation ### Getting Started - **[workflow-quickstart](workflow-quickstart.md)** - Create basic workflows with WorkflowBuilder - **[kailash-installation](kailash-installation.md)** - Installation and setup guide - **[kailash-imports](kailash-imports.md)** - Import patterns and module organization ### Core Patterns - **[node-patterns-common](node-patterns-common.md)** - Common node usage patterns - **[connection-patterns](connection-patterns.md)** - Linking nodes and data flow - **[param-passing-quick](param-passing-quick.md)** - Parameter passing strategies - **[runtime-execution](runtime-execution.md)** - Executing workflows (sync/async) - **[runtime-lifecycle](runtime-lifecycle.md)** - Runtime lifecycle, ref counting, acquire/release, context managers ### Advanced Topics - **[async-workflow-patterns](async-workflow-patterns.md)** - Asynchronous workflow execution - **[async-resource-safety](async-resource-safety.md)** - `__del__` hardening, double-check locking, pool lifecycle, static analysis guardrails - **[cycle-workflows-basics](cycle-workflows-basics.md)** - Cyclic workflow patterns - **[error-handling-patterns](error-handling-patterns.md)** - Error management strategies - **[switchnode-patterns](switchnode-patterns.md)** - Conditional routing with SwitchNode - **[pythoncode-best-practices](pythoncode-best-practices.md)** - PythonCode node best practices - **[mcp-integration-guide](mcp-integration-guide.md)** - Model Context Protocol integration ## Key Concepts ### Canonical Node Pattern (4-Parameter) **This is the single source of truth for node configuration.** All other skills reference this section. ```python workflow.add_node( "NodeClassName", # 1. Node type (PascalCase, string) "unique_node_id", # 2. Unique ID (snake_case, string) { # 3. Configuration dict "param1": "value", "param2": 123 }, connections=[] # 4. Optional: input connections ) ``` | Parameter | Type | Description | Example | | ----------- | ---- | ------------------------------------ | ------------------------------- | | Node type | str | The node class name (PascalCase) | `"LLMNode"`, `"HTTPRequest"` | | Node ID | str | Unique identifier (snake_case) | `"fetch_data"`, `"process_1"` | | Config | dict | Node-specific configuration | `{"url": "..."}` | | Connections | list | Optional input connections (4-tuple) | `[("src", "out", "dst", "in")]` | **Connection Methods**: ```python # Method 1: add_connection (4-positional params - explicit) workflow.add_connection("read_file", "content", "transform", "input") # Method 2: connect (flexible API with keyword args) workflow.connect("read_file", "transform", from_output="content", to_input="input") # Method 3: connect with mapping (multiple outputs) workflow.connect("node1", "node2", mapping={"content": "input", "meta": "metadata"}) ``` ### WorkflowBuilder Pattern - String-based node API: `workflow.add_node("NodeName", "id", {})` - Always call `.build()` before execution - Never `workflow.execute(runtime)` - always `runtime.execute(workflow.build())` ### Runtime Selection - **AsyncLocalRuntime**: For Docker/async (async contexts) - async-first, no threading, 10-100x faster - **LocalRuntime**: For CLI/scripts (sync contexts) - synchronous execution with thread support - **get_runtime()**: Auto-detection helper that selects appropriate runtime based on context Both runtimes return identical structure: `(results, run_id)` tuple. ### Runtime Architecture Both LocalRuntime and AsyncLocalRuntime inherit from BaseRuntime with shared capabilities: **BaseRuntime Foundation**: - 29 configuration parameters (debug, enable_cycles, conditional_execution, connection_validation, etc.) - Execution metadata management - Common initialization and validation modes (strict, warn, off) **Shared Mixins**: - **CycleExecutionMixin**: Cyclic workflow execution with validation - **ValidationMixin**: Workflow structure validation (5 methods) - **ConditionalExecutionMixin**: Conditional execution and branching with SwitchNode support **AsyncLocalRuntime-Specific**: - WorkflowAnalyzer for optimal execution strategy - Level-based parallelism for concurrent execution - Thread pool for sync nodes without blocking - Semaphore control to prevent resource exhaustion ## Critical Rules - ✅ ALWAYS: `runtime.execute(workflow.build())` - ✅ String-based nodes: `workflow.add_node("NodeName", "id", {})` - ✅ 4-parameter connections: `(source_id, source_param, target_id, target_param)` - ✅ Docker/async: Use AsyncLocalRuntime (mandatory) - ✅ CLI/Scripts: Use LocalRuntime - ❌ NEVER: `workflow.execute(runtime)` - ❌ NEVER: Instance-based nodes - ❌ NEVER: Use LocalRuntime in Docker (causes hangs) ## When to Use This Skill Use this skill when you need to: - Create custom workflows from scratch - Understand workflow fundamentals - Learn node patterns and connections - Set up runtime execution - Handle errors in workflows - Implement cyclic or async patterns - Integrate with MCP - Get started with Kailash SDK ## Related Skills - **[02-dataflow](../02-dataflow/SKILL.md)** - Database operations framework built on Core SDK - **[03-nexus](../03-nexus/SKILL.md)** - Multi-channel platform framework built on Core SDK - **[04-kaizen](../04-kaizen/SKILL.md)** - AI agent framework built on Core SDK - **[06-cheatsheets](../06-cheatsheets/SKILL.md)** - Quick reference patterns - **[08-nodes-reference](../08-nodes-reference/SKILL.md)** - Complete node reference - **[09-workflow-patterns](../09-workflow-patterns/SKILL.md)** - Industry workflow templates - **[17-gold-standards](../17-gold-standards/SKILL.md)** - Mandatory best practices ## Support For complex workflows or debugging, invoke: - `pattern-expert` - Workflow patterns and cyclic debugging - `testing-specialist` - Test workflow implementations --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/integrum-global) — claim your Tome and manage your conversions.