Assess project stacks against four quality gates for AI agent compatibility.
npx skills add https://github.com/pfrack/frugalis --skill 10x-stack-assess-pfrack
Please help me install this Agent Skill. Skill: 10x-stack-assess Source: https://github.com/pfrack/frugalis/tree/main/.github/skills/10x-stack-assess Command: npx skills add https://github.com/pfrack/frugalis --skill 10x-stack-assess-pfrack
This Skill assesses the compatibility of an existing project's stack with AI agents, using four quality gates to determine how well it supports AI workflows.
Run the /10x-stack-assess skill in your project directory.
High-intent search queries and answers about installing and using this skill.
To evaluate your project stack for AI agent compatibility, run a brownfield assessment that scores components against four quality gates: typed, convention-based, popular in training data, and well-documented. The output is a detailed assessment report with scores and gap analysis.
An agent-friendly stack uses typed languages, relies on conventions over configuration, utilizes components popular in training data, and maintains thorough documentation. Stack assessment tools verify these traits by scoring your components against these four specific quality gates.
Assess a brownfield project for AI workflow readiness by analyzing its existing stack against typed, convention-based, popular, and documented criteria. The process identifies failing components and suggests compensation strategies to improve agent interactions.
If your project components fail AI quality gates, you should apply suggested compensation strategies. The stack assessment generates a detailed report highlighting these gaps and providing specific strategies to compensate for failing components in agent workflows.
Yes, you can run a stack assessment on any existing project directory. The evaluation analyzes your current stack components directly, identifying gaps and generating an assessment report without requiring specific external dependencies.
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