Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI-coding power users, AI agent developers, automation builders, founders, creators, power users, and any developer using 4+ AI coding providers who needs at-a-glance visibility into per-provider usage and reset windows -- and who can pair steipete/CodexBar with macOS 14+ (Sonoma) for the OS surface, Homebrew (`brew install --cask codexbar`) or GitHub Releases for the install surface, a
Who should use it
Who should skip it
Consider steipete/CodexBar lower priority if you already have a working solution in this category.
About this signal
steipete/CodexBar is tracked by RepoRadar as a tiny macos 14+ menu bar app from in the macOS AI Provider Limits Tracker section. It was first seen on 2026-07-07 and last updated on 2026-07-07. The current verdict is 'try now' with a Silver tier and easy setup difficulty. Across RepoRadar's eight signals, steipete/CodexBar is strongest on practical usefulness (9.0) and momentum (9.0) and weakest on maturity (5.8) — a profile worth weighing against your own priorities. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned steipete/CodexBar a composite score of 7.9 out of 10, placing it in the Silver tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 1.0 and never affects the composite score or tier. The risk label of 'low' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to evaluate an AI tool before you adopt it for the checklist behind this score.
Risk explanation
The 3; 144* / 168-fork repo is at active maintenance but the privacy-first pattern reuses existing provider sessions (OAuth + device flow + API keys + browser cookies + local files) -- treat the first evaluation cycle as a smoke test (install via `brew install --cask codexbar` + open Settings > Providers + enable the providers you use + confirm the per-provider countdowns + confirm the credits/spend/cost scans + confirm the live status polling) before relying on the tracker in production; the 57-provider coverage may not cover every provider you use -- the consumer SHOULD verify the provider list covers the providers you use before deploying; the macOS 14+ (Sonoma) requirement means older macOS versions are not supported -- the consumer SHOULD verify the macOS version before deploying.