Qantcore evaluates AI agents using a transparent, multi-dimensional framework. No black-box scores, no sponsored rankings.
Composite score from: documentation quality, community activity, release cadence, API stability, and user reviews. Minimum 3 data sources required before a rating is published. Confidence interval shown when available.
Calculated from: last release date, commit frequency, documentation updates, community response time. Above 80% = actively maintained. Below 30% = stale — flagged for review.
↑↑ = accelerating (freshness > 80%, weekly releases) · ↑ = growing (freshness > 60%) · → = stable · ↓ = declining (freshness < 30%, no recent updates)
Local = runs on your hardware (Docker, Python CLI, self-hosted). Cloud = SaaS-only, requires vendor infrastructure. Hybrid solutions flagged where applicable.
Head-to-head comparisons use 9 standardized metrics. Green highlights indicate best-in-class per metric. All data is refreshed daily from official sources, documentation, and community feedback. No AI-generated scores — every rating is traceable to a data source.
Catalog updated daily. Each card shows last-updated timestamp. Stale entries (30+ days without update) are flagged. Our pipeline runs automated checks every 24 hours.