Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI engineers, designers, founders, indie hackers, content creators, growth teams, and small teams who want Claude Code / Cursor / Codex to ship a polished product-launch animation, a clickable App prototype, an editable PPT, or a print-grade infographic from a single sentence in 3-30 minutes, because alchaincyf/huashu-design is an MIT HTML-native Agent Skill for coding assistants that
Where this stands now
alchaincyf/huashu-design ranks #120 of 2143 tracked Radar items by composite score (8.5 against a section median of 6.7). The section currently carries 1038 Bronze, 646 Gold, 459 Silver. RepoRadar has retained observations for this record since 2026-06-24 (92 days in the current window). Signal extremes versus the section: momentum at the 97th percentile; novelty at the 97th percentile.
Who should use it
Who should skip it
Pass on alchaincyf/huashu-design if its scope or audience does not match what your team is building right now.
About this signal
alchaincyf/huashu-design is tracked by RepoRadar as an AI project in the Radar section. First seen 2026-06-24; the source record was last checked on 2026-06-24. The current verdict is 'try now' with a Gold tier and review needed setup difficulty. The standout signals for alchaincyf/huashu-design are novelty (10.0) and momentum (10.0), while setup ease (6.5) 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 alchaincyf/huashu-design record combines a 8.5/10 composite score with separate popularity (100.0), risk (low), and setup (review needed) 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
Risk label is still being reviewed from the captured evidence. Treat the item as unknown-risk until you review the linked source, permissions, setup path, and data access.