validate

Validate context engineering documentation structure, schemas, links, placeholders, and line numbers.

8|2|Updated Feb 5, 2026

Search Tags:#documentation #validation #schema #context engineering #links #placeholders

Ready to run

npx skills add https://github.com/SireJeff/k0ntext --skill validate-sirejeff

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: validate
Source: https://github.com/SireJeff/k0ntext/tree/main/skills/validate
Command: npx skills add https://github.com/SireJeff/k0ntext --skill validate-sirejeff

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill ensures the quality and correctness of your context engineering setup, catching errors before they impact AI performance.

Core Features & Use Cases

Comprehensive Checks: Validates directory structure, file schemas, internal links, and placeholder usage.
Accuracy Verification: Confirms line number accuracy in documentation references to code.
Use Case: Before deploying new documentation or code changes, run this Skill to guarantee that all links are valid, schemas are correct, and placeholders are resolved, ensuring a robust and error-free context for AI models.

Quick Start

Run the full validation suite for context engineering.

Frequently Asked Questions about validate

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

FAQPage Schema

How do I validate internal links and placeholders in context engineering documentation?▼

To validate internal links and placeholders in context engineering documentation, run a comprehensive validation suite that checks directory structures, schema formats, and resolves internal references to ensure setup correctness.

What is context engineering validation and when do I need it?▼

Context engineering validation is a comprehensive checking process for directory structures, JSON schemas, markdown frontmatter, and link resolution. You need it before deploying documentation to guarantee an error-free context for AI models.

How do I verify line number accuracy in documentation references against code?▼

To verify line number accuracy in documentation references against code, use an accuracy verification check that confirms documentation line numbers correctly match the actual codebase before deploying changes.

Can I validate JSON and markdown frontmatter schemas without external dependencies?▼

Yes, you can validate JSON and markdown frontmatter schemas without external dependencies by running the built-in validation suite, which performs schema validation natively to ensure resource integrity.

Why does context engineering validation fail when directory structure is incorrect?▼

Context engineering validation fails when directory structure is incorrect because the validation suite strictly checks directory paths and internal link resolution, breaking the integrity required for AI context resources.

What's the best way to ensure the integrity of AI context resources before deployment?▼

The best way to ensure the integrity of AI context resources before deployment is to run a full validation suite checking schemas, internal links, placeholders, and line numbers to catch errors early.