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better agentic engineering
This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
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.
Deployment reality
The available setup signal starts with: 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-*.vsix. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
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.
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.
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 Moderate; the latest push was 88 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.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyMIT is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
3.4k Stars
Reuse
491 Forks
Attention
3.4k Watchers
Maintenance
moderate
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-*.vsix63
Health Score
Moderate
Commit Activity
May 6, 2026
Created
Jul 18, 2026
Last push
Star history will appear after daily syncs accumulate data.
Forks
Open
Watchers
microsoft
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The agent that grows with you
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Skills for Real Engineers. Straight from my .agents directory.
anomalyco/opencode
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✓
License
✓
Forked
~ Moderate
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.