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semantic-validation

Validate analysis findings with a 4-layer consistency and accuracy stack.

Updated May 22, 2026
Search Tags:#data validation#research validation#ai analyst#analysis validation#semantic validation#analysis accuracy#4-layer validation
One-click install
npx skills add https://github.com/shekerkamma/peopletech-marketplace --skill semantic-validation-shekerkamma
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: semantic-validation
Source: https://github.com/shekerkamma/peopletech-marketplace/tree/main/plugins/ai-analyst/skills/ai-analyst/semantic-validation
Command: npx skills add https://github.com/shekerkamma/peopletech-marketplace --skill semantic-validation-shekerkamma

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analysis findings often contain inconsistencies, logical gaps, or unvalidated assumptions that reduce their reliability for decision-making. This skill provides a standardized 4-layer validation process to catch these issues, and it is fully integrated into the ask-question and run-analysis skills so you never need to invoke it manually.

Core Features & Use Cases

  • 4-Layer Validation Stack: Automatically checks analysis findings for consistency, logical coherence, data alignment, and assumption validity.
  • Seamless Integration: Built directly into core ai-analyst skills, so validation runs automatically as part of every analysis task without extra configuration.
  • Use Case: When running a product cohort analysis via run-analysis, this validation ensures your findings about user retention are accurate and free of common analytical errors before you share them with stakeholders.

Quick Start

Use the ask-question or run-analysis skill for your analysis task, and the 4-layer semantic validation will be applied automatically to your findings.

Frequently Asked Questions about semantic-validation

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

FAQPage Schema
How do I validate analysis findings for consistency and logical coherence?▼

You can validate analysis findings by running a 4-layer validation stack that automatically checks for consistency, logical coherence, data alignment, and assumption validity without manual invocation.

What is semantic validation in data and research analysis?▼

Semantic validation is a standardized 4-layer process that catches inconsistencies, logical gaps, and unvalidated assumptions in research outputs, data analysis results, and strategic insights to ensure accuracy.

How do I apply automated validation checks to a product cohort analysis?▼

Automated validation checks apply directly to product cohort analysis findings by running through the integrated ask-question or run-analysis skills, ensuring user retention insights are accurate and free of analytical errors.

Do I need to manually invoke validation for every data analysis task?▼

No manual invocation is needed for data analysis validation because the 4-layer validation stack is built directly into the ask-question and run-analysis skills and runs automatically as part of every task.

Can I use this validation process for strategic insights and research outputs?▼

Yes, you can use this validation process for strategic insights and research outputs because it satisfies standardized requirements for validating research outputs, data analysis results, and strategic findings.

What are the limitations of using built-in validation for analysis accuracy?▼

A limitation of built-in validation is that it applies exclusively to analysis tasks executed via the ask-question and run-analysis skills within the ai-analyst plugin, requiring no separate configuration but limiting external use.

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