Import external results
Turn an eval you already ran in any harness into a ranked, shareable RedCrown run.
1. Prepare the results JSON
RedCrown expects an aggregate results object with one entry per candidate. The required top-level fields are name, objective, quality_metric, quality_bar, step, and candidates.
Go to Upload (/advanced/upload). Paste your results JSON directly into the text area or load it from a file using Load file.
Prepare a results.json file in the upload schema. The required fields are name, objective, quality_metric, quality_bar, step, and candidates (an array of per-candidate aggregate scores). See the CLI reference for the full schema.
Pass the same object shape to import_results. The required fields are name, objective, quality_metric, quality_bar, step, and candidates:
{
"name": "My external eval",
"objective": "cheapest",
"quality_metric": "exact_match",
"quality_bar": 0.8,
"step": "generate",
"candidates": [...]
}2. Import
Once your results are imported, RedCrown ranks them, applies the same integrity checks as a native run, and makes the run shareable via a proof link.
After loading your results on Upload (/advanced/upload), click Import. The ranked run report appears immediately.
redcrown import-results results.jsonThe command uploads the results to your workspace and prints the run ID and a link to the ranked report in the app.
Call import_results with the full results object. The response includes the experiment ID and run ID:
{
"name": "My external eval",
"objective": "cheapest",
"quality_metric": "exact_match",
"quality_bar": 0.8,
"step": "generate",
"candidates": [...]
}Last verified .