بنقرة واحدة
cheatsheets
Kailash cheatsheets — patterns, nodes, workflows, cycles, perf, security, saga.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Kailash cheatsheets — patterns, nodes, workflows, cycles, perf, security, saga.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Claude Code architecture — artifact design, context, agentic patterns. For CC audit/build.
Kailash Core SDK — workflows, 110+ nodes, runtime, async, cycles, MCP, OpenTelemetry. Use for WorkflowBuilder + connections + runtime patterns.
Kailash DataFlow — MANDATORY for DB/CRUD/bulk/migrations/multi-tenancy. Raw SQL/ORMs BLOCKED.
Kailash Nexus — MANDATORY for HTTP/API/CLI/MCP unified deployment. Direct FastAPI/Flask BLOCKED.
Kailash Kaizen (Python) — MANDATORY for AI agents/RAG/signatures. Custom LLM agents BLOCKED.
Kailash MCP — server/client/tools/resources/auth/transports for AI agent integration.
| name | cheatsheets |
| description | Kailash cheatsheets — patterns, nodes, workflows, cycles, perf, security, saga. |
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