decision-question-builder

Name: decision-question-builder
Availability: InStock
Author: aurora-atoms

Convert bounded decision requests into structured, evidence-backed packets with JSON schema validation.

Updated Jun 1, 2026

Search Tags:#workflow #architecture #governance #evidence #decision-making #expert-review

Ready to run

npx skills add https://github.com/aurora-atoms/lattice --skill decision-question-builder

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: decision-question-builder
Source: https://github.com/aurora-atoms/lattice/tree/main/skills/decision-question-builder
Command: npx skills add https://github.com/aurora-atoms/lattice --skill decision-question-builder

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill solves the problem of context-poor requests for expert attention by transforming ambiguous decision-making tasks into structured, answerable packets that minimize expert-answer latency.

Core Features & Use Cases

Evidence-Based Framing: Automatically synthesizes known facts, material unknowns, and assumptions into a coherent decision packet.
Option Symmetry: Forces the creation of two to four comparable, distinct options to prevent biased or incomplete decision-making.
Use Case: When an architect needs a senior leader to approve a technical trade-off, this Skill prepares a packet that includes the decision, risks, and a minimum-response contract, allowing the leader to provide a one-line answer without needing to reconstruct the background.

Quick Start

Use the decision-question-builder skill to generate a decision packet for the current architecture trade-off by providing the decision, target respondent, and all relevant evidence.

Frequently Asked Questions about decision-question-builder

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

FAQPage Schema

What is a structured decision packet for architecture and product trade-offs?▼

A structured decision packet transforms ambiguous decision requests into evidence-backed packets with option symmetry, risk disclosure, and minimal-response contracts to minimize expert-answer latency for authoritative input.

How do I create an evidence-backed decision request for senior leadership?▼

Create an evidence-backed decision request by providing the bounded decision, target respondent, and relevant evidence to generate a packet with two to four comparable options and a minimum-response contract for a one-line approval.

Can I enforce option symmetry and JSON schema validation for governance decisions?▼

Yes, you can enforce option symmetry and JSON schema validation for governance decisions by generating bounded packets that require two to four distinct, comparable options satisfying structural validation requirements.

Does decision packet generation work for operational and architecture trade-offs?▼

Decision packet generation works for architecture, product, and operational decisions requiring authoritative input, converting bounded decision requests into structured formats with risk disclosure and minimal-response contracts.

What is the best way to minimize expert-answer latency on technical trade-offs?▼

The best way to minimize expert-answer latency is to frame decisions using evidence-based packets with option symmetry and minimum-response contracts, allowing leaders to approve trade-offs without reconstructing background context.

When should I not use a minimum-response contract for expert review?▼

You should not use a minimum-response contract for expert review when the decision request is unbounded or lacks sufficient material evidence, as the packet requires synthesized facts and comparable options to prevent biased decision-making.