decide

Classify rover decisions and append reasoned verdicts to the audit trail.

3|1|Updated Apr 4, 2026
One-click install
npx skills add https://github.com/epologee/leclause-skills --skill decide-epologee
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: decide
Source: https://github.com/epologee/leclause-skills/tree/main/packages/autonomous/skills/decide
Command: npx skills add https://github.com/epologee/leclause-skills --skill decide-epologee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Operators and autonomous agents often stall when confronted with choices, breaking automated loops or deferring decisions that would be better made immediately; this Skill provides a structured framework to classify decisions, apply principled defaults, and continue work without unnecessary user intervention.

Core Features & Use Cases

  • Decision classification: Identifies Mechanical, Taste, or User Challenge decisions to determine whether to act, recommend, or stop and notify.
  • Ordered principles: Applies six prioritized principles (completeness, boil the lake, pragmatic, DRY, explicit, bias toward action) with phase-aware tiebreakers to choose robust defaults.
  • Research and fallbacks: Detects and optionally invokes research skills (/whywhy, /ground, /inspiratie, /gurus), logs missing skills to the loop file, and records every verdict in a Decision Audit Trail on disk for traceability.
  • Use Case: Invoked by a rover at a fork in traversal or by a developer running /autonomous:decide to resolve tradeoffs during code modifications while preserving an auditable trail.

Quick Start

Invoke the decide skill with a concise description of the choice you face and let it classify the decision, apply principles, optionally run research skills, and append the outcome to the loop file decision audit trail.

Frequently Asked Questions about decide

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

FAQPage Schema
How do I automate decision-making for an autonomous agent or rover?

Autonomous agent decision-making can be automated by classifying choices as mechanical, taste, or user challenges, applying ordered principles to produce a reasoned verdict without stalling. This prevents automated loops from breaking when confronting tradeoffs.

What is decision classification for autonomous systems and when is it needed?

Decision classification identifies choices as mechanical, taste, or user challenge decisions to determine whether an autonomous system should act, recommend, or stop and notify. It is needed when operators or agents face forks during operational traverses or task handoffs.

How do I create an audit trail for autonomous agent decisions?

You create a decision audit trail by appending a row to the loop file on disk every time a verdict is reached. This records the classified decision, applied principles, and any fallbacks, ensuring traceability for autonomous operations.

Can I use research skills during autonomous decision-making?

Yes, you can use research skills during autonomous decision-making. The framework detects and optionally invokes available research skills like /whywhy, /ground, /inspiratie, or /gurus, while logging missing skills to the loop file as fallbacks.

What principles are applied to resolve tradeoffs in autonomous code modifications?

Resolving tradeoffs in autonomous code modifications applies six ordered principles: completeness, boil the lake, pragmatic, DRY, explicit, and bias toward action. Phase-aware tiebreakers choose robust defaults when conflicts arise.