hermes-rubric
Evidence-first LLM-as-judge scoring for AI artifacts — papers, PRs, prompts, cold emails: synthesizes a rubric, collects quoted-evidence citations, scores only against that evidence, and hedges on thin evidence. Every dimension ties to a file:line or quote, with reproducibility receipts. 7 backends.
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Per-day rates divide a measured star count by the days it covers: the interval between two snapshots for Rising fastest, the age of the repository for New and fast. They are not fixed 24-hour changes, and stars show interest, not quality.