What problem does it solve?
This Skill helps teams evaluate how well an existing software stack supports AI-assisted development. It turns a broad question about agent-friendliness into a structured assessment of the project’s language, framework, tooling, and surrounding conventions, with concrete guidance for reducing friction.
Core Features & Use Cases
- Project Stack Detection: Inspects the current codebase for language, framework, build tool, test runner, package manager, CI/CD, deployment setup, and existing instruction files.
- Quality Gate Scoring: Assesses each detected component against four criteria: type safety, convention strength, ecosystem popularity within its language family, and documentation quality.
- Compensation Guidance: Produces ready-to-paste instruction file rules for stacks that fall short, so teams can improve agent effectiveness without replacing their technology choices.
- Use Case: A team inheriting a brownfield application can use this Skill to understand where AI agents will work smoothly, where extra steering is needed, and what project instructions should be added before deeper maintenance or health checks.
Quick Start
Ask the AI to assess the current project stack for agent-friendliness and generate a stack assessment for the brownfield codebase.
