turing

Trace logic steps to locate the first divergence from expected outputs.

4|Updated Apr 30, 2026
One-click install
npx skills add https://github.com/satsilem/claude-skills-pantheon --skill turing
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: turing
Source: https://github.com/satsilem/claude-skills-pantheon/tree/main/skills/turing
Command: npx skills add https://github.com/satsilem/claude-skills-pantheon --skill turing

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify where a logic or reasoning step diverges from expected results by tracing execution step by step, stating the produced outputs and the point at which they diverge.

Core Features & Use Cases

  • Step-by-step trace of logic across code, prompts, or decision trees, with explicit state and outputs.
  • Divergence detection: locate the first mismatch between expected and actual results.
  • Explicit assumption tracking and state validation to surface hidden premises.
  • AI prompt analysis and model-output debugging to improve reliability.

Quick Start

Provide the input process you want traced and the expected result, and I will walk through the logic to locate the first divergence.

Frequently Asked Questions about turing

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

FAQPage Schema
How do I trace logic step by step to find where an algorithm produces unexpected results?

To trace logic step by step, provide the input process and expected result; the system walks through execution states to locate the first divergence where actual output mismatches expectations.

What is logic tracing and how does it help with debugging reasoning or AI prompts?

Logic tracing is a step-by-step execution analysis technique for debugging reasoning, AI prompts, or algorithms; it surfaces hidden premises and validates state to detect exact divergence points.

How do I debug an AI prompt that generates incorrect outputs?

Debug an AI prompt by providing the prompt and expected output for step-by-step execution path analysis; the system tracks explicit assumptions and state validation to locate the first reasoning divergence.

What do I need to provide to start a logic trace for an algorithm audit?

Starting a logic trace requires a clearly stated starting state, explicit assumptions, a single trace path to examine, and the expected result to compare against actual execution outputs.

Can I use this logic tracing approach for decision trees and process workflows?

Yes, logic tracing works across decision trees, processes, code, and AI prompts; it examines explicit state and outputs at each step to pinpoint where actual execution diverges from expected results.

Why does my reasoning output diverge from the expected result despite correct assumptions?

A reasoning output diverges when a hidden premise or intermediate state produces an unexpected result; step-by-step logic tracing validates each explicit assumption to locate the exact divergence point.