Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for builders and creators who want a more structured way to plan, batch, and revisit GPT-image-2 or OpenAI-compatible image jobs while keeping project state on their own machine.
Who should use it
Who should skip it
Skip mrslimslim/gpt-image-canvas if you cannot isolate its execution environment or audit what data it touches before connecting anything sensitive.
About this signal
mrslimslim/gpt-image-canvas is tracked by RepoRadar as a app in the AI Imaging section. It was first seen on 2026-06-26 and last updated on 2026-06-26. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. Across RepoRadar's eight signals, mrslimslim/gpt-image-canvas is strongest on workflow potential (9.3) and maturity (8.9) and weakest on setup ease (6.4) — 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 mrslimslim/gpt-image-canvas a composite score of 8.2 out of 10, placing it in the Gold 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 681.0 and never affects the composite score or tier. The risk label of 'medium' 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 app stores provider credentials locally in SQLite and can also fall back to a Codex login path, so shared machines should be checked carefully before any production keys are added; Optional cloud backup can push generated assets to Tencent COS or S3 and R2-compatible storage, so sensitive creative work should stay local until storage settings are reviewed; The README's example environment still references a forward-looking gpt-5.5 Responses model placeholder, so users should verify the exact live model names their provider actually supports before copying defaults into production configs.