think-core

Apply inductive, deductive, or abductive reasoning to analyze problems.

1|Updated Apr 13, 2026
One-click install
npx skills add https://github.com/danielsimonjr/deepthinking-plugin --skill think-core
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: think-core
Source: https://github.com/danielsimonjr/deepthinking-plugin/tree/main/skills/think-core
Command: npx skills add https://github.com/danielsimonjr/deepthinking-plugin --skill think-core

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The think-core skill provides structured access to three fundamental reasoning patterns—Inductive, Deductive, and Abductive—enabling users to generalize from observations, derive conclusions from rules, and identify best explanations for surprising observations.

Core Features & Use Cases

  • Inductive reasoning: generalize from multiple observations to extract patterns.
  • Deductive reasoning: apply explicit premises to derive specific conclusions.
  • Abductive reasoning: generate and compare explanations for anomalies; optionally structure multi-step abduction.

Quick Start

Provide a target problem and specify the reasoning mode (inductive, deductive, or abductive) to execute.

Frequently Asked Questions about think-core

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

FAQPage Schema
What is the difference between inductive, deductive, and abductive reasoning?

Inductive reasoning generalizes patterns from multiple observations, deductive reasoning derives specific conclusions from explicit premises, and abductive reasoning generates and compares explanations for anomalies. This triad covers generalization, derivation, and diagnosis.

How do I structure multi-step reasoning to diagnose anomalies?

To diagnose anomalies, apply abductive reasoning using explicit abductiveSteps to generate and compare explanations. This structures the reasoning chain by labeling each step to select the best explanation for surprising results.

Can I use structured reasoning to derive conclusions from explicit rules?

Yes, you can apply deductive reasoning to execute derivationSteps. By providing explicit premises, the reasoning chain applies rules to derive specific conclusions with clear step labeling.

What is the best way to extract patterns from multiple observations?

The best way to extract patterns is applying inductive reasoning through inductionSteps. This process generalizes from multiple observations to identify and structure patterns across the provided data.

Do I need prior logic training to use structured reasoning patterns?

No prior logic training is required. You simply provide a target problem and specify the reasoning mode (inductive, deductive, or abductive), and the guided multi-step process structures the explanations automatically.

When should I not use abductive reasoning for problem analysis?

Abductive reasoning is not suitable when you need absolute certainty, as it generates best explanations for surprising observations rather than deriving guaranteed conclusions. Use deductive reasoning instead for strict rule-based derivation.