think

Route reasoning tasks to thinking modes and emit schema-aligned JSON outputs.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Route reasoning tasks to the appropriate thinking mode, enabling targeted method application and consistent outputs.

Core Features & Use Cases

  • Parse the user invocation to determine an explicit mode or rely on the mode-index decision tree for auto-selection.
  • Load the corresponding category skill, apply its method, and produce a structured JSON output aligned with the mode's schema.
  • Support end-to-end routing across the 34 modes with a single entry point and clear fallbacks.

Quick Start

Invoke /think bayesian "update my belief that the service is down given new evidence" to see Bayesian updating in action.

Frequently Asked Questions about think

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

FAQPage Schema
How do I route reasoning tasks to the appropriate thinking mode automatically?

You can route reasoning tasks automatically by relying on the mode-index decision tree to select the appropriate thinking mode, apply its method, and generate a structured JSON output.

How does structured output routing work for AI reasoning architectures?

Structured output routing works by parsing the invocation, loading the corresponding category skill, applying its method, and emitting a JSON object aligned with the chosen mode's schema.

Can I explicitly select a specific reasoning mode like Bayesian updating?

Yes, you can explicitly select a reasoning mode like Bayesian updating by specifying it in the invocation, which bypasses the auto-recommendation decision tree.

What is the best way to manage multiple reasoning modes from a single entry point?

The best way to manage multiple reasoning modes is using a single entry point that supports end-to-end routing across 34 modes with clear fallbacks for consistent structured outputs.

Do I need to specify a reasoning mode if I want structured output?

No, you do not need to specify a mode manually; the skill can auto-recommend a mode using its decision tree and still produce a structured JSON output matching the mode's schema.

What happens when a reasoning task does not match a specific mode?

When a reasoning task does not match an explicitly requested mode, the system applies an auto-recommendation decision tree to route the task and provides clear fallbacks for structured output.