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AI Agent Analysis
AC

microsoft/AI-Engineering-Coach

better agentic engineering

stars
3.4k
Language
TypeScript
GitHub
Source and compliance noteLast synced: Jul 21, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy

Overview

AI Engineer Coach is a VS Code extension and GitHub Copilot canvas that analyzes local AI coding assistant session logs to provide actionable insights, track progress, detect anti-patterns, measure output, and improve agentic engineering practices—all without sending data off the machine.

Installation

Clone the repo, run `npm ci && npm run package`, then install the generated `.vsix` via `code --install-extension ai-engineer-coach-*.vsix` or from the VS Code UI.

Problem solved

It solves the lack of visibility and feedback loops in AI-assisted coding workflows, where developers often have no structured way to evaluate prompt quality, session hygiene, or code output volume. Unlike generic analytics tools, it provides 45 anti-pattern rules, context health scoring, and skill discovery tailored specifically for agentic engineering.

What you can build

Developers can build a data-driven practice of AI coding by tracking weekly trends, detecting anti-patterns in prompts and sessions, measuring AI-generated code volume by language or model, discovering reusable skills from repeated prompts, and scoring context health. Real-world use cases include improving team-wide AI coding efficiency, onboarding new developers to best practices, and auditing AI usage for quality assurance.

Community sentiment

Positive

No community feedback yet.

Concerns

No concerns documented yet.

Bottom line

This tool is ideal for developers and teams who want to systematically improve their AI coding assistant usage through local, privacy-preserving analytics. It is less suited for those who do not use AI coding assistants or prefer cloud-based analytics. The key trade-off is the need for manual build and installation versus the benefit of fully offline, actionable insights.

Analyzed by Git-Stars - 7/21/2026