Eval
You own the experiment design. Plan, blind, run, synthesize.
Non-negotiables for blinding:
- No
eval,test,judge,experiment,rubric,score,compare,benchmark,candidate, orarenain any directory, file, or prompt the candidate sees. - The candidate prompt looks like an organic user request. State the goal, not the meta.
- No chain-eliciting cues. Don't ask the candidate to list which skills, principles, or files they applied. Ask for design notes generally and grade chain-following from code shape, not self-report.
- Sanitize directory and slug names. Use project-shaped names a user might pick.
- Don't tell the candidate other candidates exist.
- The judge can know it's judging but sees outputs by sanitized label only, never by model name.
- Comparing two variants: one judge scores both sets in a single pass on one scale, blind to which set each came from.
Steps:
- Frame. State what variant is under test and what behavior counts as success. Write the rubric (3-6 concrete criteria) for the judge only. Hold it back from candidates.
- Set up sanitized environments. Per-candidate working dir with the variant in place. Plant any context an organic task would have: a project skeleton, the skills the candidate would naturally read.
- Author one organic prompt. What a user would type. No leakage of what's being measured.
- Spawn N parallel candidates on different models per the arena skill's Phase B. Each works in its own sanitized dir. Same prompt to each.
- Spawn one blinded judge on a different model family per the arena skill's Phase C. Judge sees outputs by sanitized label and the rubric, never a model name.
- Verify the chain from transcripts, not self-report. Read each candidate's local transcript under the active workspace's
agent-transcripts/directory (the system prompt names this path). Do not glob across~/.cursor/projects/*/. That crosses workspace boundaries and reads private chats from unrelated projects. Look at which files each candidate actually opened. Grade chain-following from the files it really read plus the shape of the code, never from the candidate's own claims. - Read every candidate output yourself end to end. Compare to the judge's verdict. Disagreement means a model is biased or the rubric is ambiguous. Synthesize.
Reply: variant under test, rubric, per-candidate notes, judge's verdict, your synthesis, and a recommendation for whether to promote the variant.