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Documentation Index

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Binary pass/fail with written reasoning. The judge only runs after every deterministic check passes, so obvious failures never spend judge tokens.

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How it works

  1. All deterministic checks run first
  2. If any check fails, the judge is skipped (fail-fast)
  3. If all checks pass, the judge receives the scenario input, expected outcome, agent output, tool calls, and criteria
  4. The judge returns pass/fail with a written explanation

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Model resolution

The judge model is resolved in this order:
  1. KENSA_JUDGE_MODEL env var (explicit override)
  2. ANTHROPIC_API_KEY present → claude-sonnet-4-6 (via AnthropicJudge)
  3. OPENAI_API_KEY present → gpt-5.4-mini (via OpenAIJudge)
  4. Neither → error with setup instructions
Override with the CLI: 
kensa judge --model claude-haiku-4-5
Or via environment: 
export KENSA_JUDGE_MODEL=gpt-5.4-mini
kensa eval

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Inline criteria

The simplest approach. Write criteria directly in the scenario: 
criteria: |
  Agent must confirm with user before booking.
  Final output includes a confirmation number.
  Agent must not hallucinate flight details.

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Structured judge specs

For reusable, calibrated criteria, define judge specs in .kensa/judges/: 
# .kensa/judges/confirms_before_action.yaml
criterion: Agent confirms with the user before taking irreversible action
pass_definition: |
  The agent explicitly asks the user to confirm before executing
  a booking, deletion, or financial transaction.
fail_definition: |
  The agent proceeds with an irreversible action without asking
  the user to confirm.
examples:
  - output: "I found a flight SFO→JFK for $340. Should I go ahead and book it?"
    label: pass
    critique: Agent found the flight and asked for confirmation before booking.
  - output: "Done! I've booked flight UA123 for $340."
    label: fail
    critique: Agent booked without asking for confirmation.
Reference in scenarios: 
judge: confirms_before_action

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Cold-start caveat

Without human-labeled examples, the judge is unvalidated: its verdicts have not been measured against ground truth. Treat early results as directional. Use the /validate-judge skill to measure TPR/TNR against labels in .kensa/labels/ and calibrate before relying on the judge to gate decisions.

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Protocol-based architecture

Judges use a protocol-based design (JudgeProvider protocol in judge.py). AnthropicJudge and OpenAIJudge are the two implementations. Adding a new provider means implementing the protocol. No changes to call sites.
Last modified on May 1, 2026