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AI Engineer Coach

better agentic engineering.
Analyze your AI coding assistant usage — any harness, one dashboard.

License: MIT VS Code 1.115+


585890575-d60203ce-c678-4fdd-918e-f6c04bff04df.mp4


What it does

AI Engineer Coach reads your local AI session logs and turns them into actionable insights — no data leaves your machine.

  • Track progress -- practice scores, weekly trends, daily activity charts
  • Detect anti-patterns -- 45 rules across prompt quality, session hygiene, code review, tool mastery, and context management
  • Measure output -- AI-generated code volume by language, workspace, model, and harness
  • Discover skills -- find repeated prompts and turn them into reusable skills
  • Score context health — agentic readiness checks, instruction-file audits, workspace context maps
Screenshots

Timeline

Code Output

Premium Request Consumption

Activity Patterns - Projects

Activity Patterns - Work Hours

Anti-Patterns

Skill Finder

Context Quality

Context Management

Learning Center

Achievements

Agentic SDLC

Share Your Stats


Installation

The extension is not published to a marketplace or Releases page, so you build the .vsix yourself and install it. Pick whichever build path fits your setup.

Path 1 -- Dev Container build (no local Node.js/npm)

Prerequisites:

  • VS Code
  • Dev Containers extension
  • Docker or Podman

Steps:

  1. Clone the repo and open it in VS Code.
  2. Reopen in container.
  3. Run:
npm ci
npm run package
  1. Install the generated .vsix (see Install the built VSIX below).

Path 2 -- Local build

Prerequisites:

  • VS Code
  • Node.js and npm

Steps:

git clone https://github.com/microsoft/ai-engineering-coach.git
cd ai-engineering-coach
npm ci
npm run package

Then install the generated .vsix (see below).

Install the built VSIX

macOS / Linux

code --install-extension ai-engineer-coach-*.vsix

Windows / PowerShell

code --install-extension (Get-ChildItem . -Filter 'ai-engineer-coach-*.vsix' | Select-Object -First 1).FullName

If the CLI does not work, install it from the VS Code UI: press Ctrl+Shift+P, type Install from VSIX, then browse to the .vsix file and select it.

After install:

  1. Open the command palette (Cmd+Shift+P / Ctrl+Shift+P)
  2. Run AI Engineer Coach: Open Dashboard
  3. Navigate pages from the sidebar, filter by workspace or harness

Run as a canvas in the GitHub Copilot app

The same dashboard also runs as a canvas inside the GitHub Copilot app, so you do not need VS Code to use it.

A canvas is an interactive side panel in the GitHub Copilot app. Rather than replying only in chat, the agent can open a canvas to show rich, task-specific UI that you view and interact with directly while you keep working. Extensions register their own canvases, and this repo ships one named AI Engineer Coach under .github/extensions/ai-engineer-coach/. It reuses the exact webview bundle from the VS Code extension and parses your local session logs in process, so nothing leaves your machine.

To open it:

  1. Clone this repo and open it as a project in the GitHub Copilot app.
  2. Build the project once:
npm install && npm run build
  1. Open the AI Engineer Coach canvas. On a fresh clone it shows a setup card with the build command and reloads into the full dashboard once the build finishes. No manual reopen needed.

A few features depend on the local VS Code language model and are hidden in canvas mode: Skill Finder, Learning Center, the Level Up section, and the Context Health AI review. Everything driven by your on-disk logs (Dashboard, Timeline, Coding Moments, Output, Patterns, Anti-Patterns) works the same. App sessions show up as GitHub Copilot App and terminal sessions as GitHub Copilot CLI in the harness breakdown.


Pages

Observe

Page Description
Dashboard Practice scores with week-over-week trends, daily activity chart, top workspace stats
Timeline Gantt-style session timeline with per-day drill-down and overlap detection
Coding Moments Screenshot gallery from AI coding sessions with story reels and workspace filtering

Measure

Page Description
Output Generated code volume by language, model usage table (token breakdown temporarily hidden)
Burndown Monthly AI token budget progress with projections (temporarily disabled)
Patterns 7×24 activity heatmap and work-life balance signals

Improve

Page Description
Anti-Patterns Five practice score cards with severity ratings, concrete actions, and example prompts. 45 editable markdown rules plus a coverage heatmap
Rule Editor Create, edit, and tune detection rules visually or as raw markdown. Live-test against your data
Rule Playground Interactive REPL for the rule DSL with field browser, function catalog, and metric list
Data Explorer Browse session fields, view distributions, run ad-hoc filters
Skill Finder Discover repeated prompt patterns and matching community skills from the open-source catalog
Context Health Overall context score, agentic readiness checklist, workspace context map, AI-powered instruction-file review

Level Up

Page Description
Learning Center Personalized quizzes and code-comparison rounds generated from your actual usage
Achievements XP-based progression with Bronze → Silver → Gold → Diamond tiers
Agentic SDLC How you use AI across the full software-development lifecycle
Share Generate a shareable stat card and export Markdown/JSON summaries

Privacy

  • Read-only — the extension never modifies your session files
  • Local analysis — all parsing and analytics run entirely on your machine
  • No proprietary telemetry — the extension does not phone home or collect usage data
  • Optional AI features — some features (rule compiler, skill finder, context review) use the VS Code built-in Copilot language model API when explicitly invoked by the user

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

License

MIT

Disclaimer

This project is an open-source community effort by Microsoft employees. It is not an official Microsoft product and is not part of any Microsoft service or support offering. It is provided as-is with no warranties or guarantees.

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