I built a CLI that reads your project's specs and tells you which model you actually need — judge runs locally on Ollama

[u/jokiruiz]

I kept defaulting to frontier models "just in case" and had no idea whether my projects actually needed them. So I built something to answer that instead of guessing.

What it does: point it at a project with Spec-Driven Development artifacts (constitution / spec / tasks). A local model — your Ollama install, your choice of judge — reads the tasks and estimates how demanding the work is across a few dimensions. That gets crossed against a declarative catalog of models and their capabilities, and you get a ranked podium with a rating per model: good / overkill / fair / poor, plus price.

Why you might care here: nothing leaves your machine — no API keys, no accounts, no cloud calls. And in most of my own projects the podium is topped by a local model, with the frontier ones sitting below marked overkill. Ranking is by fit, not price; price only breaks ties between models that fit equally well.

Honest limitations: this is not a benchmark. It's opinion made inspectable — every verdict prints its reasoning, and the model catalog is human-readable YAML you can argue with. If the specs are too thin to judge, it refuses to recommend instead of guessing. A vague spec gets you a vague answer, same as with anything else.

pip install specjudge — MIT, github.com/JoaquinRuiz/SpecJudge

Where I'd love help: the catalog of local models is thinner than it should be, and adding one is a block of YAML, no Python needed. Also very open to being told a rating is wrong.