decision

Facilitate evidence-based route judgments for quest next steps.

Updated Jul 1, 2026
One-click install
npx skills add https://github.com/louzhengshuai/seepscientist --skill decision-louzhengshuai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: decision
Source: https://github.com/louzhengshuai/seepscientist/tree/main/src/skills/decision
Command: npx skills add https://github.com/louzhengshuai/seepscientist --skill decision-louzhengshuai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps researchers and AI agents make complex route judgments in quests, ensuring informed decisions based on evidence and avoiding ambiguity.

Core Features & Use Cases

  • Evidence-Based Decision Making: Guides users through the process of making decisions based on durable evidence.
  • Route Judgments: Supports judgments such as go, stop, branch, reuse-baseline, write, finalize, reset, or user-decision transitions.
  • Use Case: For instance, when a quest reaches a point where the next step is not obvious, the decision skill can be used to gather evidence, evaluate options, and choose the best course of action.

Quick Start

Use the decision skill to make a route judgment in your quest by providing the evidence and rationale.

Frequently Asked Questions about decision

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

FAQPage Schema
How do I make evidence-based route judgments when a research quest reaches an unclear next step?

Evidence-based route judgments resolve ambiguous quest steps by gathering durable evidence, evaluating options, and selecting actions like go, stop, or branch to determine the next step. This ensures informed decisions are based on structured criteria rather than guesswork.

What route judgment actions can I use to manage quest progression?

Route judgment actions include go, stop, branch, reuse-baseline, write, finalize, reset, and user-decision transitions. These actions guide quest progression by determining the exact operational step needed based on evaluated evidence.

When do I need user interaction for decision-making criteria in quest automation?

User interaction for decision-making criteria is needed when preference resolution is required during quest automation. It facilitates evidence-based decisions by prompting the user to resolve ambiguities and select the best course of action when the next step is not obvious.

Can I automate research workflows without manual preference resolution for every route judgment?

Research automation relies on durable evidence and structured decision-making principles to minimize manual preference resolution. However, when criteria conflict or evidence is insufficient, user interaction is required to resolve preferences and proceed.

What is the best way to structure evidence analysis for complex research automation tasks?

The best way to structure evidence analysis is applying durable evidence-based decision-making principles to evaluate route options. This involves gathering evidence, assessing action alternatives, and using structured criteria to select the optimal course of action.

Does this approach work without structured decision-making principles in place?

Structured decision-making principles are required for effective route judgments. Without them, the evidence gathering and action selection process cannot systematically determine the next step, leading to ambiguity and uninformed choices in quests.