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validation-patterns

Validate Kailash SDK workflows for parameters, connections, structure, DataFlow, imports, and security.

Updated Oct 10, 2025
Search Tags:#security audit#code hygiene#workflow validation#kailash#import validation#dataflow compliance#CI regression
One-click install
npx skills add https://github.com/FFOO6866/lead2cash --skill validation-patterns-ffoo6866
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: validation-patterns
Source: https://github.com/FFOO6866/lead2cash/tree/main/.claude/skills/16-validation-patterns
Command: npx skills add https://github.com/FFOO6866/lead2cash --skill validation-patterns-ffoo6866

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It helps developers prevent common Kailash SDK failures by enforcing validation patterns for parameters, connections, workflow structure, DataFlow compliance, imports, and security before execution and release.

Core Features & Use Cases

  • Validate workflow inputs and structure to catch missing parameters, invalid connection contracts, duplicate node IDs, dead ends, and missing entry/exit points.
  • Enforce DataFlow and access conventions to ensure correct result access shape, string ID preservation, and multi-instance isolation patterns.
  • Harden code quality and safety with absolute-import validation, security checks for secrets/SQL injection/path traversal, and repeatable hygiene marker scrubbing (including a three-layer regex gate).
  • Use the orphan detection playbook to find public-surface classes that never run in production hot paths and to require paired fixes or deletions.

Quick Start

Ask the skill to validate a workflow for parameter, connection, structure, DataFlow compliance, import style, and security before you call workflow.build() and run the pipeline.

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 SDK workflow before building and executing the pipeline?▼

Workflow validation checks parameters, connections, structure, and DataFlow compliance before you call workflow.build(). It catches missing parameters, invalid connection contracts, and duplicate node IDs to prevent runtime failures.

Why does my Kailash DataFlow pipeline fail when accessing results from multi-node workflows?▼

DataFlow access failures often stem from incorrect result-access shapes or broken string ID preservation. Enforcing multi-instance isolation patterns and validating access conventions before execution ensures pipeline seams hold during runtime.

What's the best way to catch security issues like SQL injection and path traversal during SDK code review?▼

Security checks for secrets, SQL injection, and path traversal are enforced during code review. The validation applies security-sensitive code patterns and absolute-import validation to harden pipeline safety before release.

How do I find unused public-surface classes in my SDK that never run in production hot paths?▼

The orphan detection playbook identifies public-surface classes that never execute in production hot paths. It requires paired fixes or deletions to ensure code hygiene and remove dead code from the pipeline.

Can I automate CI regression testing for workflow structure and DataFlow compliance checks?▼

Release-blocking end-to-end regression fingerprinting automates CI regression for workflow structure and DataFlow compliance. It validates pipeline seams and enforces required validation order to prevent defects from reaching runtime.

Does Kailash SDK validation require a specific import style to pass code hygiene checks?▼

Absolute-import validation is required to pass code hygiene checks. The process includes repeatable hygiene marker scrubbing using a three-layer regex gate to ensure imports comply with security and quality standards.

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