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kev-finetune

jaredpalmer/kevSkill

Fine-tune a Kev decision model (open Jev-style System One model) on a user's own workload and serve it with calibrated probabilities. Interviews the user, finds existing Jev/TypeSafe questions or labelled data in their codebase, generates enough synthetic training data to measure a gain, trains and calibrates on Modal, scores against the released checkpoint, deploys a TypeSafe-compatible endpoint, and tears everything down. Use when someone wants noul/choice/score questions answered on their own domain (routing, triage, moderation, classification, scoring), wants calibrated confidence for auto

Scanned · 1 to knowSkillSource: GitHubContains scripts
9,326 stars +289 this week Updated 19d ago License Apache-2.0 Context ≈153 tokens always loaded
79popular

Why this score

Stars21/35
Usage (forks)8/15
Upkeep25/25
License15/15
Owner history10/10

This repo hosts 10 skills, so its 9,326 stars are split between them (about 933 each) for scoring.

Popularity score: 79/100 from public GitHub signals only. It shows how widely used and maintained this is, not how well it works. Not included yet: the fake-star check. The security scan is shown separately and doesn't change the score. How we rank

Security

Scanned Oct 20, 2026 at commit 1f04cfa28e6a, with Cisco's open-source skill-scanner.

What its code does:

Web addresses in its code:

These are the sites named in the code, so it's where your data could go. It isn't a complete list: code can build addresses while it runs, and a few of these may be links rather than calls. Whatever you send also goes to the AI model you use.

A scan lists patterns in the code. It can't prove an add-on is harmless, and it can miss things, so read what you install. How we scan

Alternatives

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