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emergent-value-audit

Analyze design and training context to surface implicit value weightings and produce a pre-deployment risk report.

6|1|Updated Mar 5, 2026
Search Tags:#pre-deployment#risk-assessment#ai-governance#value-audit#emergent-values#value-weightings
One-click install
npx skills add https://github.com/Forexgod21/YVYC-Claude-Skills --skill emergent-value-audit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: emergent-value-audit
Source: https://github.com/Forexgod21/YVYC-Claude-Skills/tree/main/agentic/emergent-value-audit
Command: npx skills add https://github.com/Forexgod21/YVYC-Claude-Skills --skill emergent-value-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Emergent-value-audit surfaces implicit AI preferences and weightings that emerge through design and training, revealing gaps between intended values and actual behavior before deployment.

Core Features & Use Cases

  • Intended Value Inventory: document explicit optimization targets, constraints, and priorities.
  • Emergent Value Signal Detection: analyze design, data, and observed behaviors to surface proxy values and weightings.
  • Intended vs Emergent Comparison: map emergent findings to the intended inventory and flag gaps.
  • Deployment Risk Assessment: assign risk levels with scenario-based justifyications.
  • Pre-Deployment Recommendations: provide concrete actions to align deployment with stated values.

Quick Start

Install this skill and run a pre-deployment emergent value audit on your AI system to surface implicit preferences.

Frequently Asked Questions about emergent-value-audit

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

FAQPage Schema
What is a pre-deployment AI value audit?▼

A pre-deployment AI value audit identifies implicit value weightings and proxies that emerge through design and training, comparing them against intended objectives to reveal behavioral gaps before release.

How do I detect emergent values in my AI system before release?▼

To detect emergent values, analyze the system's design, training context, and observed behaviors to surface proxy values and weightings, then map them to your intended value inventory for comparison.

How do I assess deployment risks for misaligned AI values?▼

Assess deployment risks by assigning risk levels to the gaps between intended and emergent values, using scenario-based justifications to prioritize concrete actions that align behavior with stated objectives.

Can I document intended AI optimization targets and constraints?▼

Yes, you can document explicit optimization targets, constraints, and priorities into an intended value inventory, which serves as the baseline for comparing against observed emergent behaviors.

What is the best way to close gaps between intended and emergent AI values?▼

The best way to close value gaps is to generate a structured pre-deployment report with concrete recommendations and risk assessments that align the system's emergent behaviors with its intended values.

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