Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
avkash/DeepWorks matches RepoRadar's tracked scope on the repository's own declared topics (artificial-intelligence, deep-learning, generative-models, llm, machine-learning, pytorch), and is currently maintained: 335 stars and a push on 2026-10-10. This record states only what the repository states about itself; RepoRadar has not run it.
Where this stands now
avkash/deepworks ranks #551 of 1581 tracked Developer Tools items by composite score (4.9 against a section median of 4.9). The section currently carries 1324 Bronze, 153 Silver, 103 Gold, 1 Low Signal.
Who should use it
Who should skip it
Hold off on avkash/deepworks until it graduates from watchlist status with stronger evidence.
About this signal
avkash/deepworks is tracked by RepoRadar as a code repository in the Developer Tools section. First seen 2026-10-10; the source record was last checked on 2026-10-10. The current verdict is 'watch' with a Bronze tier and unknown setup difficulty. The standout signals for avkash/deepworks are open-source/build quality (7.4) and evidence quality (7.2), while momentum (3.5) trails — that balance shapes where it fits best. This page summarizes the evidence RepoRadar captured from https://github.com/avkash/DeepWorks.
How this item is evaluated
The avkash/deepworks record combines a 4.9/10 composite score with separate popularity (0.0), risk (conditional), and setup (unknown) 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
Discovered automatically from GitHub metadata and not installed, run, or reviewed by RepoRadar; Scout-staged and not hands-on tested by RepoRadar. Evidence level is Official; confirm the vendor's current install, pricing, and access terms before adopting.