audit-decision-psychology

Audit user complaint clusters through Kahneman's dual-system decision-psychology lens.

Updated Apr 21, 2026

Search Tags:#audit #evidence #user-feedback #clusters #kahneman #decision-psychology #audit-json

Ready to run

npx skills add https://github.com/speplinski/hackathon-opus-47 --skill audit-decision-psychology

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: audit-decision-psychology
Source: https://github.com/speplinski/hackathon-opus-47/tree/main/skills/audit-decision-psychology
Command: npx skills add https://github.com/speplinski/hackathon-opus-47 --skill audit-decision-psychology

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill audits a labelled cluster of user complaints about a digital product using Kahneman's dual-system decision-psychology lens to reveal how cognitive biases shape user decisions.

Core Features & Use Cases

Analyzes clusters produced by upstream feedback pipelines to diagnose decision architecture flaws (defaults, framing, loss aversion, endowment effects).
Outputs a structured JSON audit detailing four dimensions—Cognitive Load & Ease, Choice Architecture, Judgment & Heuristics, Temporal Experience—plus intent, evidence pointers, and per-finding severity.

Quick Start

Provide a labelled cluster with quotes and optional context to run the audit and emit a JSON artifact.

Frequently Asked Questions about audit-decision-psychology

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

FAQPage Schema

How do I audit user feedback for cognitive biases and decision architecture flaws?▼

You audit user feedback by processing labelled complaint clusters through Kahneman's dual-system decision-psychology lens to diagnose defaults, framing, and loss aversion. This produces a structured JSON audit detailing Cognitive Load, Choice Architecture, Judgment Heuristics, and Temporal Experience dimensions.

What is decision psychology auditing for digital product complaints?▼

Decision psychology auditing dissects how choice architecture influences user decisions by analyzing complaint clusters. It evaluates cognitive load, framing, and heuristics using quotes, ui_context, html, and screenshot evidence to generate severity-rated findings.

How do I analyze clustered user complaints using Kahneman's dual-system framework?▼

Provide a labelled cluster with quotes and optional context to run the audit. The framework evaluates cognitive ease, choice architecture, judgment heuristics, and temporal experience, emitting a structured JSON artifact with evidence pointers and per-finding severity ratings.

Can I audit feedback clusters without screenshots or HTML context?▼

You can audit clusters using quotes alone, but screenshots and HTML context strengthen the evidence pointers. The audit grounds its severity ratings and findings in available ui_context, html, and screenshot evidence to maximize accuracy.

Does this approach work with feedback clusters from any upstream pipeline?▼

It applies to clusters produced by any upstream feedback pipeline as long as the input includes labelled complaints and quotes. The audit outputs structured JSON with four decision-psychology dimensions, intent, and severity ratings regardless of the clustering source.

What format does the decision psychology audit output?▼

The audit outputs a structured JSON artifact containing four dimensions—Cognitive Load & Ease, Choice Architecture, Judgment & Heuristics, and Temporal Experience—along with explicit intent, evidence pointers, and severity ratings grounded in user feedback quotes.