decision-critic

Stress-test architectural decisions with structured adversarial analysis via a Python orchestration script.

1|Updated Jan 12, 2026
One-click install
npx skills add https://github.com/akiselev/qt-llm-template --skill decision-critic-akiselev
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: decision-critic
Source: https://github.com/akiselev/qt-llm-template/tree/main/.claude/skills/decision-critic
Command: npx skills add https://github.com/akiselev/qt-llm-template --skill decision-critic-akiselev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Structured adversarial critique to stress-test decisions and reveal hidden assumptions, preventing overconfidence in critical design choices.

Core Features & Use Cases

  • Decompose decisions into claims, assumptions, and constraints for traceable critique
  • Verify claims with independent checks and multiple reasoning paths
  • Synthesize verdicts with actionable recommendations and risk signals

Quick Start

Provide your decision statement and run the script to start the critique workflow.

Frequently Asked Questions about decision-critic

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

FAQPage Schema
How do I stress-test architectural decisions for hidden assumptions?

Stress-test architectural decisions by providing your design choice to an adversarial critique workflow, which decomposes claims, verifies assumptions, and synthesizes a traceable verdict with risk signals.

What is adversarial analysis for software architecture trade-offs?

Adversarial analysis is a structured critique process that targets high-stakes design choices and technology selections, enforcing decomposition of claims and independent verification to reveal hidden assumptions.

How do I critique a technology selection before committing to it?

Critique a technology selection by submitting the decision statement to a Python orchestration script that runs structured adversarial analysis, verifying assumptions via multiple reasoning paths.

Can I use this for high-stakes design choices without external dependencies?

Yes, high-stakes design choices can be analyzed without external dependencies, as the workflow relies solely on a Python orchestration script to synthesize actionable recommendations.

What is the best way to verify architectural assumptions and constraints?

The best way to verify architectural assumptions is through structured adversarial analysis, which enforces independent checks and multiple reasoning paths to expose overconfidence in critical design choices.

When should I not use structured adversarial critique for decisions?

Structured adversarial critique should not be used for low-stakes or trivial decisions, as the rigorous scrutiny and claim decomposition process is specifically designed for high-stakes architectural trade-offs.