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better agentic engineering
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microsoft/AI-Engineering-Coach is tracked as a TypeScript project in the AI Agent area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 3.4k total stars, with +61 today, +0 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Active; the latest push was 3 days ago, and the open issue queue is 49, about 1.45% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 491 forks and 3.4k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need TypeScript teams evaluating ecosystem-native tooling. Be cautious when you need a legal review, security audit, or production SLA.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 61. Follow the original GitHub repository for final install, security, and release information.
Momentum
3.4k Stars
Reuse
491 Forks
Attention
3.4k Watchers
Maintenance
active
License
MIT
Open issues
49
AI Engineer Coach is a VS Code extension that analyzes local AI coding assistant session logs to provide actionable insights, including practice scores, anti-pattern detection, code output metrics, and skill discovery, all without sending data off the machine.
Key Features
- Tracks practice scores, weekly trends, and daily activity charts - Detects 45 anti-patterns across prompt quality, session hygiene, code review, tool mastery, and context management - Measures AI-generated code volume by language, workspace, model, and harness
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
git clone https://github.com/microsoft/ai-engineering-coach.git && cd ai-engineering-coach && npm ci && npm run package && code --install-extension ai-engineer-coach-*.vsix83
Health Score
Active
Commit Activity
May 6, 2026
Created
Jul 18, 2026
Last push
+0
Today's growth
+0
7-day growth
+0
30-day growth
Forks
Open
Watchers
microsoft
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✓
License
✓
Forked
✓ Active
Maintained
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.
Capabilities
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.
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.