InternScience/SciEvalKit
A unified evaluation toolkit and leaderboard for rigorously assessing the scientific intelligence of large language and vision–language models across the full research workflow.
Star & Fork Trend (14 data points)
Multi-Source Signals
Growth Velocity
InternScience/SciEvalKit has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | SciEvalKit | Agent-World-Protocol | eval-view | Claude-Skills |
|---|---|---|---|---|
| Stars | 79 | 79 | 80 | 80 |
| Forks | 10 | 4 | 17 | 21 |
| Weekly Growth | +0 | -7 | +0 | +2 |
| Language | Python | Rust | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | N/A | Apache-2.0 | NOASSERTION |
Capability Radar vs Agent-World-Protocol
Last code push 5 days ago.
Fork-to-star ratio: 12.7%. Active community forking and contributing.
Issue data not yet available.
No measurable growth in the current period (first-day cold start expected).
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.