rune-sequential-thinking

Analyzes multi-variable decisions through dependency-ordered reasoning with bias detection and second-order effect tracking.

1|Updated Mar 22, 2026
One-click install
npx skills add https://github.com/dangvu008/VietTruyen --skill rune-sequential-thinking-dangvu008
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rune-sequential-thinking
Source: https://github.com/dangvu008/VietTruyen/tree/main/.agents/skills/rune-sequential-thinking
Command: npx skills add https://github.com/dangvu008/VietTruyen --skill rune-sequential-thinking-dangvu008

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Complex decisions with many interdependent variables often lead to poor outcomes because factors are evaluated out of order, biases go unchecked, and downstream consequences are ignored. This Skill structures that reasoning into an ordered, auditable decision process. ## Core Features & Use Cases - Dependency-Ordered Evaluation: Identifies all variables, maps which ones constrain or influence others, and resolves them in dependency order with a running state block. - Reversibility Classification: Classifies decisions as two-way door, one-way door, or partially reversible, scaling analytical effort accordingly. - Bias and Second-Order Checks: Cross-checks for anchoring, status quo, and overconfidence biases, and traces second-order effects for irreversible decisions. - Use Case: When planning a system architecture where the database choice constrains the ORM, which constrains the API design, use this Skill to resolve each decision in the correct order and produce a final recommendation with a confidence level. ## Quick Start Ask the AI to run a sequential analysis on your architecture decision, listing the interacting variables and constraints, and request a final recommendation with confidence level.

Frequently Asked Questions about rune-sequential-thinking

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

FAQPage Schema
How do I analyze a decision with many interacting variables?

List every variable, map which ones constrain or influence others, then resolve them in dependency order from most-constrained to most flexible. This Skill automates that process and produces a structured decision tree with a final recommendation.

When should I use sequential thinking instead of simple pros and cons?

Use it when a decision has more than three interacting variables and choosing one option changes what is valid for the others. For single-dimension or linear problems, a simpler problem-solving approach is more efficient.

What is a one-way door versus two-way door decision?

A two-way door decision is reversible with low switching cost, so it deserves light analysis and a review date. A one-way door decision is irreversible and high-stakes, requiring full sequential analysis including second-order effects and bias checks.

How does the skill detect cognitive biases in decision making?

It cross-checks for three biases: anchoring (did the first resolved variable over-constrain the rest), status quo (was the current approach unfairly favored), and overconfidence (are confidence levels justified). Detected biases are reported with their impact on the recommendation.

What happens if there is a dependency cycle between variables?

The cycle is flagged explicitly and broken by treating one variable as a fixed assumption. The analysis then proceeds in dependency order from that assumption, and the assumption is noted in the final report.

What are the limitations of sequential decision analysis?

It is stateless with no memory between calls, and it is inefficient for simple linear problems. When more than eight variables exist, related ones must be grouped into composite variables to keep the analysis tractable.