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10x-stack-assess

Assess project stacks against 4 quality gates for AI agent workflows.

Updated Jun 9, 2024
Search Tags:#quality gates#project assessment#stack assessment#compensation strategies#AI agent compatibility
One-click install
npx skills add https://github.com/Kuba312/daily-board --skill 10x-stack-assess-kuba312
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: 10x-stack-assess
Source: https://github.com/Kuba312/daily-board/tree/main/frontend/.agents/skills/10x-stack-assess
Command: npx skills add https://github.com/Kuba312/daily-board --skill 10x-stack-assess-kuba312

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Assess how well your project stack supports AI agent workflows with 4 quality gates: typed, convention-based, popular in training data, well-documented.

Core Features & Use Cases

  • Assessment: Score each component of your stack against 4 quality gates.
  • Compensation Strategies: Provide specific recommendations for improvement if any gates fail.
  • Documentation: Output a structured assessment in a markdown file for easy reference.

Quick Start

Assess your stack with the command '10x-stack-assess'.

Frequently Asked Questions about 10x-stack-assess

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

FAQPage Schema
How do I assess my project stack for AI agent compatibility?▼

Assess project stack AI agent compatibility by scoring components against 4 quality gates: typed, convention-based, popular in training data, and well-documented. The evaluation outputs a structured markdown file for easy reference during brownfield development.

What makes a software stack compatible with AI agent workflows?▼

A software stack is compatible with AI agent workflows if it passes 4 quality gates: typed, convention-based, popular in training data, and well-documented. These gates determine how effectively AI agents can understand and manipulate the codebase.

How do I improve project stack compatibility when quality gates fail?▼

Improve failed quality gates by applying specific compensation strategies generated during the stack assessment. These strategies provide targeted recommendations to enhance typed structures, conventions, documentation, and training data familiarity.

Can I evaluate an existing brownfield project for AI agent-friendliness?▼

Evaluate existing brownfield projects by running the assessment command in the project directory. It requires access to the project directory and related metadata files to score the current stack against established quality gates.

What are the limitations of evaluating stack compatibility for AI workflows?▼

Evaluating stack compatibility relies on 4 specific quality gates and requires direct access to project directory metadata files. It targets software engineers during brownfield development and outputs structured markdown rather than automated code refactoring.

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