Create decision-pack Interactively

Interview users to collect config options and generate a complete generate_dpack() input.

Updated Mar 19, 2026

Search Tags:#automation #scaffold #docker #interview #environment #decision-pack #dlab

Ready to run

npx skills add https://github.com/benmaier/decision-agent-placeholder --skill create-decision-pack-interactively

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Create decision-pack Interactively
Source: https://github.com/benmaier/decision-agent-placeholder/tree/main/.claude/skills/create-dpack-interactive
Command: npx skills add https://github.com/benmaier/decision-agent-placeholder --skill create-decision-pack-interactively

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Guide a human through creating a dlab decision-pack by interviewing them and then calling generate_dpack() with the right config.

Core Features & Use Cases

Interactive interview to gather required details for a new decision-pack (name, description, tooling, modal needs, and optional features).
Generates a complete, Docker-sandboxed decision-pack scaffold via generate_dpack() with the collected config.
Provides a reusable template and workflow to set up agent environments quickly, even for complex setups.

Quick Start

Start by telling me what you want to build and I will interview you and generate a complete dlab decision-pack using generate_dpack().

Frequently Asked Questions about Create decision-pack Interactively

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

FAQPage Schema

How do I scaffold a new decision-pack for dlab?▼

To scaffold a dlab decision-pack, you provide your desired configuration details through an interactive interview, which then generates a complete, ready-to-run decision-pack environment via generate_dpack().

What is a dlab decision-pack used for?▼

A dlab decision-pack is used to configure a Docker-sandboxed agent environment. It encapsulates tooling, package managers, and parallel agent settings to standardize and isolate automated workflows.

What configuration options do I need to set up a decision-pack?▼

Setting up a decision-pack requires specifying the project name, description, tooling choices like package managers, modal requirements, parallel agents, and any optional features needed for the environment.

Can I create a Docker-sandboxed agent environment without manual configuration?▼

Yes, you can create a Docker-sandboxed agent environment without manual configuration by answering interview questions about your tooling and modal needs, which generates a complete Docker-sandboxed decision-pack scaffold automatically.

How does interactive scaffolding handle complex decision-pack setups?▼

Interactive scaffolding handles complex decision-pack setups by guiding you step-by-step through an interview to collect all required configuration details, ensuring the generate_dpack() function receives a complete and valid input.

Are there limitations to creating decision-packs interactively?▼

The interactive creation process is limited by the options gathered during the interview, meaning any complex Docker-sandboxed configurations or agent environment features outside the provided interview parameters cannot be generated.