docs

Getting Started

The app's built-in help for this screen, as shipped in quodeq 1.13.1. Edit this page on GitHub

The first time you launch quodeq, a welcome opens with the two ways in: a repository to evaluate, or an evaluations repository to connect so you can read results your team already published (Shared Repository).

Your first evaluation

  1. Press add project on the Repositories tab, or pick the first way in on the welcome.
  2. Paste a git url or choose a local folder. For a url, quodeq keeps a working copy under ~/quodeq/repos (set QUODEQ_REPOS_DIR to change that); results always live under ~/.quodeq.
  3. The model is the one chosen in Settings, else the best one found on this machine once you pick its model (AI Providers). The standard is the quodeq default unless you change it on Evaluate.
  4. Press scan and run.

For a url, a progress bar shows the clone with the percentage and size so far, and the evaluation starts when the clone lands. A local folder needs no clone and starts at once. You can close the panel while a clone runs: it keeps going in the background and a tile on the Repositories tab shows the same bar. No evaluation starts for a clone you closed early.

Drafts are saved

The panel remembers what you typed. If you close it midway, your draft comes back next time.

To see the welcome again later, open Settings, find the onboarding section and press show welcome.

What happens next

  • The Evaluate tab streams the run live, including findings as they appear.
  • When it finishes, the Overview tab opens with grades and top findings.
  • Violations, Map, and History let you drill in from different angles.
  • To reach your results from another machine or share them with your team, connect an evaluations repository from the Repositories tab. import evaluations restores a previously exported archive.

Requirements

  • Python 3.12+. The dashboard UI ships pre-built, so Node.js is not required.
  • At least one AI provider configured. See AI Providers.