validation-patterns

Name: validation-patterns
Availability: InStock
Author: Dchuuuuuu

Validates Kailash SDK workflows for parameter, connection, import, DataFlow, and security compliance.

Updated Apr 2, 2026

Search Tags:#workflow #code review #validation #compliance #security audit #dataflow #kailash sdk

Ready to run

npx skills add https://github.com/Dchuuuuuu/disease-risk-classifier --skill validation-patterns-dchuuuuuu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: validation-patterns
Source: https://github.com/Dchuuuuuu/disease-risk-classifier/tree/main/.claude/skills/16-validation-patterns
Command: npx skills add https://github.com/Dchuuuuuu/disease-risk-classifier --skill validation-patterns-dchuuuuuu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Kailash SDK workflows fail at runtime when developers use wrong connection formats, missing parameters, relative imports, or insecure patterns. This Skill provides validation checklists and code patterns to catch these errors before execution, commit, or deployment. ## Core Features & Use Cases - Workflow Structure Validation: Enforces the 4-parameter connection pattern, string-based node API, mandatory .build() calls, and snake_case naming conventions. - Security & Import Auditing: Detects hardcoded secrets, SQL injection risks, code injection risks, and relative imports in SDK code. - DataFlow Compliance Checking: Verifies result access patterns like results["node_id"]["result"], string ID preservation, and @db.model decorator usage. - Use Case: Before committing a new workflow, run through the pre-execution checklist to confirm all connections use the 4-parameter format, all required node parameters are present, and no hardcoded API keys exist. ## Quick Start Ask the AI to validate my Kailash workflow code for gold standards compliance and list any violations with fixes.

Frequently Asked Questions about validation-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I validate a Kailash workflow before execution?▼

Call workflow.build() before runtime.execute(), which raises WorkflowValidationError for invalid parameters or connections. You can also use the WorkflowValidator class with validate_all() to collect errors and warnings in one pass.

How to check workflow connections for errors in Kailash SDK?▼

Connections must use the 4-parameter format: add_connection(source_id, source_param, target_id, target_param). Validation checks that both nodes exist, parameter names match node inputs and outputs, and no circular dependencies exist.

What security checks should I run on workflow code?▼

Check for hardcoded secrets, SQL injection via string concatenation in queries, code injection in PythonCodeNode, and file path traversal. Use grep patterns to find hardcoded API keys and prefer environment variables and parameterized queries.

Why does my workflow fail with WorkflowValidationError?▼

Common causes include missing required node parameters, wrong parameter types, unknown parameters not in the node contract, missing .build() before execute, or 3-parameter connections instead of the required 4-parameter format.

Does DataFlow validation require specific result access patterns?▼

Yes, DataFlow results must be accessed as results["node_id"]["result"], not attribute access like results["node_id"].result. Validation also checks string ID preservation, one DataFlow instance per database, and proper @db.model decorator usage.