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.