القائمة
Kailash cheatsheets: patterns, nodes, workflows, cycles, performance, security, multi-tenancy, saga, custom nodes.
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استنادا إلى تصنيف SOC المهني
Kailash DataFlow - zero-config data operations framework with automatic model-to-node generation and Data Fabric Engine. Use when asking about 'database operations', 'DataFlow', 'database models', 'CRUD operations', 'bulk operations', 'database queries', 'database migrations', 'multi-tenancy', 'multi-instance', 'database transactions', 'PostgreSQL', 'MySQL', 'SQLite', 'MongoDB', 'pgvector', 'vector search', 'document database', 'RAG', 'semantic search', 'existing database', 'database performance', 'database deployment', 'database testing', 'TDD with databases', 'external data sources', 'data products', 'db.source', 'db.product', 'db.start', 'fabric engine', 'source adapters', 'REST source', 'webhooks', or 'data fabric'. DataFlow is NOT an ORM - it generates 11 workflow nodes per SQL model, 8 nodes for MongoDB, and 3 nodes for vector operations.
Kailash Nexus - zero-config multi-channel platform for deploying workflows as API + CLI + MCP simultaneously. Use when asking about 'Nexus', 'multi-channel', 'platform deployment', 'API deployment', 'CLI deployment', 'MCP deployment', 'unified sessions', 'workflow deployment', 'production deployment', 'API gateway', 'session management', 'health monitoring', 'enterprise platform', 'plugins', 'event system', or 'workflow registration'. Also covers K8s integration: 'K8s probes', 'healthz', 'readyz', 'startup probe', 'ProbeManager', 'ProbeState', 'OpenAPI', 'openapi.json', 'OpenApiGenerator', 'security headers', 'CSRF middleware', 'CSRFMiddleware', 'SecurityHeadersMiddleware', 'middleware presets', 'Preset', or 'HSTS'.
Kailash Kaizen - production-ready AI agent framework with signature-based programming, multi-agent coordination, and enterprise features. Use when asking about 'AI agents', 'agent framework', 'BaseAgent', 'multi-agent systems', 'agent coordination', 'signatures', 'agent signatures', 'RAG agents', 'vision agents', 'audio agents', 'multimodal agents', 'agent prompts', 'prompt optimization', 'chain of thought', 'ReAct pattern', 'Planning agent', 'PEV agent', 'Tree-of-Thoughts', 'pipeline patterns', 'supervisor-worker', 'router pattern', 'ensemble pattern', 'blackboard pattern', 'parallel execution', 'agent-to-agent communication', 'A2A protocol', 'streaming agents', 'agent testing', 'agent memory', 'agentic workflows', 'AgentRegistry', 'OrchestrationRuntime', 'distributed agents', 'agent registry', '100+ agents', 'capability discovery', 'fault tolerance', 'health monitoring', 'trust protocol', 'EATP', 'TrustedAgent', 'trust chains', 'secure messaging', 'enterprise trust', 'credential rotation', 'trust verificati
Kailash dev guides: custom nodes, MCP, async, testing, deployment, RAG, security, monitoring, SDK internals.
Workflow templates: finance, healthcare, logistics, manufacturing, retail, ETL, RAG, document processing, API.
SDK release and Git workflow guides for the Kailash Python SDK including PyPI publishing, CI/CD pipelines, documentation deployment, and Git workflows. Use when asking about 'deployment', 'release', 'PyPI publish', 'CI/CD', 'GitHub Actions', 'documentation deployment', 'TestPyPI', 'wheel building', 'version bump', 'changelog', 'Git workflow', 'Git branching', 'package release', or 'multi-package coordination'.
| name | cheatsheets |
| description | Kailash cheatsheets: patterns, nodes, workflows, cycles, performance, security, multi-tenancy, saga, custom nodes. |
Comprehensive collection of quick reference guides, common patterns, and best practices for Kailash SDK development.
Use when asking about quick tips, cheat sheet, quick reference, common mistakes, node selection, workflow patterns library, cycle patterns, production patterns, performance optimization, monitoring, security config, multi-tenancy, distributed transactions, saga pattern, custom nodes, PythonCode data science, ollama integration, directoryreader patterns, or environment variables.
This skill provides quick access to:
from kailash.workflow.builder import WorkflowBuilder
from kailash.runtime import LocalRuntime
workflow = WorkflowBuilder()
workflow.add_node("NodeType", "node_id", {"param": "value"})
runtime = LocalRuntime()
results, run_id = runtime.execute(workflow.build())
# Data processing
workflow.add_node("PythonCode", "transform", {"code": "..."})
# API calls
workflow.add_node("HTTPRequest", "api", {"url": "...", "method": "GET"})
# AI/LLM
workflow.add_node("LLMNode", "chat", {"model": os.environ["LLM_MODEL"], "prompt": "..."})
workflow.add_node("LoopNode", "loop", {"max_iterations": 5})
workflow.add_node("ProcessNode", "process", {})
workflow.add_connection("loop", "item", "process", "input")
workflow.add_connection("process", "output", "loop", "feedback")
| Rule | Why |
|---|---|
| ❌ NEVER use raw SQL | Use DataFlow instead |
✅ ALWAYS call .build() | Before runtime.execute() |
| ❌ NEVER use relative imports | Use absolute imports |
| ❌ NEVER mock in Tier 2-3 | Use real infrastructure |
| ❌ NEVER train sklearn/torch directly | Use km.train(...) (skill 34-kailash-ml) |
| ✅ Cap parallel worktrees at 3 concurrent Opus agents | Beyond 3, budget exhaustion & merge conflicts dominate |
Use this skill when you need:
For cheatsheet-related questions, invoke:
pattern-expert - Pattern selection and usagedecide-framework skill - Choose appropriate patterns for your use case