Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
ClawGUI ships a complete GUI-agent development stack instead of yet another isolated training script or evaluation harness. The five-module split (RL, Eval, Agent, Skills, APP) means you can take a single agent from training through evaluation to deployment without switching frameworks or rewriting glue code. The headline result -- 17.1 MobileWorld SR with a 2B parameter model trained end-to-end
Who should use it
Who should skip it
Move on from ZJU-REAL/ClawGUI if the licensing terms, language support, or platform requirements do not fit your project.
About this signal
ZJU-REAL/ClawGUI is tracked by RepoRadar as a code repository in the AI tooling section. First seen 2026-07-12; the source record was last checked on 2026-07-12. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. The standout signals for ZJU-REAL/ClawGUI are workflow potential (9.6) and maturity (9.1), while setup ease (6.4) trails — that balance shapes where it fits best. This page summarizes the public evidence on the linked source page and states where additional review is still needed.
How this item is evaluated
The ZJU-REAL/ClawGUI record combines a 8.5/10 composite score with separate popularity (100.0), risk (low), and setup (moderate) signals. See the scoring methodology for the current weights and evidence definitions.
Putting this into practice? Read How to evaluate an AI tool before you adopt it for the checklist behind this score.
Risk explanation
Project was released 2026-04-13 (~3 months ago); the ecosystem around ClawGUI-2B is still building (1,310 stars is moderate for a research framework of this scope); Online RL training requires parallel Docker environments and real Android devices, which is a non-trivial infra footprint for individual researchers; Real-device deployment (ClawGUI-Agent + ClawGUI-APP) depends on Shizuku and ADB permissions; cloud deployment patterns are not yet documented; The 5-module split (RL / Eval / Agent / Skills / APP) means each module has its own release cadence and documentation; verify which modules you need before committing.