castorini/nuggetizer

nuggetizer-eval

Use when analyzing nuggetizer metrics outputs — comparing runs, computing agreement between models, reporting token usage and latency from trace fields, and building side-by-side evaluation tables. Use after running metrics to interpret and compare results.

Idioma del texto original: inglés

nuggetizer-install

Set up a nuggetizer development environment — checks Python 3.11+, installs via uv or pip, and verifies with doctor. Use when someone is onboarding, setting up a fresh clone, or troubleshooting their environment.

Idioma del texto original: inglés

nuggetizer-verify

Use when validating nuggetizer batch outputs — checks JSONL integrity, duplicate qids, missing nugget fields, assignment label validity, and metrics consistency. Wraps `nuggetizer validate` plus custom assertions. Use after running create, assign, or metrics…

Idioma del texto original: inglés

nuggetizer-quickstart

Use when working with nuggetizer CLI commands (create, assign, metrics), prompt templates, JSONL formats, or introspection (doctor, describe, schema, validate). Covers all entry points, flags, and the YAML prompt system.

Idioma del texto original: inglés