microsoft/AI-Engineering-Coach

Health v2 · maintenance only

Flags: no_releases young

Adoption not part of the score

3730 stars · 520 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A VS Code extension that analyzes local AI coding assistant session logs (across any harness) and turns them into actionable insights via a dashboard. It tracks practice scores, detects 45 anti-patterns, measures AI-generated code output, finds reusable skills, and scores context health — all locally with no data leaving the machine.

Use cases

• analyze my AI coding assistant usage patterns
• detect anti-patterns in how I prompt AI coding tools
• measure how much code AI generates in my projects
• find repeated prompts and turn them into reusable skills
• audit my instruction files and workspace context quality
• track weekly trends in my agentic coding practice
• see which models and harnesses I use most

When to choose

• you use AI coding assistants (Copilot, Claude Code, etc.) and want to improve your agentic engineering habits
• you want privacy-first analytics that keep session data local
• you want a single dashboard across multiple AI coding harnesses
• you want actionable coaching on prompt quality, session hygiene, and context management

When to avoid

• you need a published marketplace extension with one-click install (you must build the .vsix yourself)
• you don't use AI coding assistants at all
• you need team-level or cloud-synced analytics rather than local, per-machine insights
• you use an editor other than VS Code 1.115+

Facets

plugin · maturity active

analytics developer-tools monitoring data-visualization developer-tools artificial-intelligence analytics editor-plugin cross-platform vscode-extension ai-coding-assistants agentic-engineering session-log-analysis prompt-quality local-privacy copilot-analytics desktop

Member repositories

For agents

markdown · JSON · MCP: product_card(name="microsoft/AI-Engineering-Coach")