conversation-intake

Converts unstructured app descriptions into standardized build-spec.json and design-brief.json files for automated workflows.

7|1|Updated Mar 11, 2026
One-click install
npx skills add https://github.com/PMDevSolutions/Aurelius --skill conversation-intake
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: conversation-intake
Source: https://github.com/PMDevSolutions/Aurelius/tree/main/.claude/skills/conversation-intake
Command: npx skills add https://github.com/PMDevSolutions/Aurelius --skill conversation-intake

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Users with app ideas but no existing design files struggle to translate vague, unstructured descriptions into the standardized, machine-readable artifacts required for automated app build pipelines, often requiring excessive back-and-forth to clarify requirements.

Core Features & Use Cases

  • Structured Requirement Gathering: Conducts a maximum of 7 targeted interview questions to extract all necessary app details, auto-skipping questions already answered by initial user input or local project context.
  • Context-Aware Intake: Auto-discovers local project framework, existing components, and design tokens to avoid redundant questions and align outputs with existing project constraints.
  • Pipeline-Ready Artifacts: Generates a standardized build-spec.json and design-brief.json that integrate directly with downstream build, design, and testing phases of the Aurelius framework.
  • Use Case: A founder with a clear idea for a SaaS dashboard but no design file can answer a few short questions to get all the specs needed to auto-generate a fully built, tested React app.

Quick Start

Use the conversation-intake skill to generate a complete build specification and design brief from your natural language description of the app you want to build.

Frequently Asked Questions about conversation-intake

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

FAQPage Schema
How do I convert natural language app ideas into build specifications without design files?▼

To convert natural language app ideas into build specifications without design files, this Skill extracts requirements through a maximum of seven targeted interview questions. It auto-skips answered questions and uses local project context to generate pipeline-compatible build spec and design brief artifacts.

What is the most efficient way to generate a design brief from an unstructured app description?▼

Generating a design brief from an unstructured app description involves analyzing local project frameworks and existing components. This Skill minimizes required user input by auto-discovering design tokens, outputting a standardized design-brief.json file for downstream automated build workflows.

Can I use conversational intake to create build specs for an automated app development pipeline?▼

Yes, you can use conversational intake to create build specs for an automated app development pipeline. It produces machine-readable artifacts, specifically a build-spec.json file, that integrate directly with downstream design, build, and testing phases.

Do I need existing design files to generate a standardized build spec for a SaaS dashboard?▼

No, you do not need existing design files to generate a standardized build spec for a SaaS dashboard. The conversational intake process leverages natural language descriptions and local project context to extract all necessary app details without requiring prior design assets.

How many questions do I need to answer to produce a pipeline-ready build spec?▼

You need to answer a maximum of seven targeted questions to produce a pipeline-ready build spec. The Skill auto-skips any questions already answered by your initial app description or auto-discovered local project context to minimize input friction.

What are the limitations of using conversational intake for build spec generation?▼

A limitation of using conversational intake for build spec generation is its reliance on a maximum of seven targeted questions. If your app idea is highly complex or lacks local project context, the generated artifacts may require further manual refinement before entering downstream build phases.