What EngGauge AI does
EngGauge AI points at an engineer's GitLab or GitHub handle, reads their merged pull/merge requests, reviewer comments, and code changes, and produces a weighted assessment against a target competency level. Every claim in the generated evaluation cites a specific merge request or pull request as evidence.
Key Features
- Your Competency Model — Custom levels, dimensions, weights, and 1–4 behavioral anchors. Export and share rubrics as JSON across your engineering team.
- 100% Client-Side Privacy — No backend server. Access tokens and API keys live safely inside your Chrome profile. Works with local Chrome on-device AI or your own OpenAI, Anthropic, or Gemini API keys.
- Evidence Thresholds & Fairness — Withholds level verdicts when evidence is sparse, flags single-repository sample bias, and marks unmeasured skills as unscored rather than low.
- Self-Assessment Mode — Enables engineers to run evaluations on themselves in the second person to prepare for growth conversations and promo packets.
- Markdown Report Export — Export complete evaluation reports with linked PR citations and caveats for 1-on-1s and performance reviews.
Who it's for
Engineering managers, tech leads, and software engineers who want data-informed, fair performance conversations grounded in real code and review evidence. EngGauge AI is free on the Chrome Web Store and runs in any Chromium browser.
FAQ
Is EngGauge AI free? Yes — free to install from the Chrome Web Store.
Does it send my code or reviews to an external server? No. EngGauge AI runs entirely in your browser. All requests go directly to GitHub/GitLab and your chosen AI model provider.
Which platforms are supported? GitHub, GitHub Enterprise, GitLab, and self-hosted GitLab instances.