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ai-verification-guardrails

Implement a 3-tier verification system for data quality and AI output safety.

Updated Aug 27, 2026
Search Tags:#data quality#verification#ai#hallucination detection#guardrails#financial advice
One-click install
npx skills add https://github.com/roaming-rockenfels/ghostfolio --skill ai-verification-guardrails
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-verification-guardrails
Source: https://github.com/roaming-rockenfels/ghostfolio/tree/main/.claude/skills/ai-verification-guardrails
Command: npx skills add https://github.com/roaming-rockenfels/ghostfolio --skill ai-verification-guardrails

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) components.

What problem does it solve?

This Skill ensures the quality, safety, and reliability of AI-generated outputs by implementing a robust 3-tier verification system, preventing financial advice misinterpretations and hallucinations.

Core Features & Use Cases

  • Tier 1 (Data Freshness): Verifies that input data is up-to-date, checking trading day staleness and FX freshness.
  • Tier 2 (Calculation Integrity): Validates the accuracy of financial calculations, including portfolio consistency and performance bounds.
  • Tier 3 (AI Output Guardrails): Detects and mitigates risks in AI responses, such as financial advice, hallucinations, and incomplete answers.
  • Use Case: When an AI assistant provides portfolio performance analysis, this Skill first checks if the underlying market data is current (Tier 1), then verifies the calculation of the performance metrics (Tier 2), and finally ensures the AI's advice is safe and factually grounded (Tier 3).

Quick Start

Use the ai-verification-guardrails skill to add new verification checks for Tier 2 calculation integrity.

Frequently Asked Questions about ai-verification-guardrails

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

FAQPage Schema
How do I implement guardrails for AI hallucination detection in financial applications?▼

AI hallucination detection is implemented through a 3-tier verification system that validates data freshness, checks calculation integrity, and applies AI output guardrails to prevent financial advice misinterpretations.

What is the best way to verify data freshness and calculation integrity for portfolio analysis?▼

Data freshness and calculation integrity are verified by checking trading day staleness and FX freshness, then validating portfolio consistency and performance bounds to ensure accurate financial calculations.

How does a 3-tier verification system prevent financial advice misinterpretations from AI outputs?▼

A 3-tier verification system prevents financial advice misinterpretations by checking input data staleness, validating calculation accuracy, and detecting unsafe or ungrounded advice in the final AI response.

How do I add new calculation integrity checks to an existing verification module?▼

You add new calculation integrity checks by modifying the API's verification module, specifically targeting the Tier 2 validation logic for portfolio consistency and performance bounds.

Does implementing AI output guardrails require prior knowledge of verification tiers?▼

Yes, implementing AI output guardrails requires understanding the 3-tier verification system and how to apply its data freshness, calculation integrity, and hallucination detection logic within your application.

Can I use this verification system to check trading day staleness and FX data freshness?▼

Yes, the verification system checks trading day staleness and FX data freshness during its Tier 1 data quality validation phase to ensure input data is current before processing calculations.

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