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tayari-diagnostics-and-tooling

Validate Tayari platform component health and LLM engine configuration.

Updated Jan 20, 2026
Search Tags:#debugging#monitoring#validation#llm#diagnostics#ats
One-click install
npx skills add https://github.com/Harshodai/tayari-skill-boost --skill tayari-diagnostics-and-tooling
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tayari-diagnostics-and-tooling
Source: https://github.com/Harshodai/tayari-skill-boost/tree/main/.claude/skills/tayari-diagnostics-and-tooling
Command: npx skills add https://github.com/Harshodai/tayari-skill-boost --skill tayari-diagnostics-and-tooling

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, pyyaml, and includes scripts (resource) components.

What problem does it solve?

This skill eliminates guesswork by providing deterministic measurements for your career operations platform, ensuring you know exactly whether your AI engine is running real models or fallbacks and whether your system components are healthy.

Core Features & Use Cases

  • Mock Detection: Instantly verify if the AI engine is using a real LLM or a mock fallback to prevent trusting fake output.
  • ATS Scoring: Run a deterministic, structural analysis of your resume against a job description to identify high-impact improvements.
  • System Health: Monitor the connectivity of your Go gateway, Python AI engine, and database to ensure the entire pipeline is operational.

Quick Start

Run the diagnostic script to check if the Python AI engine is currently configured with a real LLM or is defaulting to the mock engine.

Frequently Asked Questions about tayari-diagnostics-and-tooling

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

FAQPage Schema
How do I check if my AI engine is running a real LLM or falling back to a mock implementation?▼

You can detect mock fallbacks by running the diagnostic script to verify the Python AI engine's configuration status. This mock detection instantly checks whether a real LLM is active.

How do I run deterministic ATS scoring for a resume against a job description?▼

To perform deterministic ATS scoring, run the diagnostic script to execute a structural analysis of your resume against a job description. This identifies high-impact improvements through exact measurements.

Can I monitor the system health of Go and Python microservices in my career operations platform?▼

Yes, you can monitor system health by running diagnostic probes to check the connectivity of your Go gateway, Python AI engine, and database. This ensures the entire career pipeline remains operational.

Do I need Python and shell access to validate my career pipeline components?▼

Yes, validating career pipeline components requires standard shell environment access and Python 3 to execute diagnostic probes and test suites, alongside dependencies like pytest and pyyaml.

What is the best way to verify the operational integrity of an ATS career platform?▼

The best way to verify operational integrity is to run deterministic test suites that perform system health checks, LLM engine verification, and ATS scoring across Go and Python microservices.

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