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Exports turn review sessions into evidence that product and engineering can act on.

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Export formats

Eval Labs supports structured exports such as:
  • JSON
  • CSV
  • Markdown
Use JSON when engineering needs full structure. Use CSV when comparing scores across many items. Use Markdown when sharing human-readable summaries.

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What to check in a good export

A complete export should include:
  • session metadata
  • run source
  • prompt count
  • custom suite linkage when relevant
  • cases
  • Lucia responses
  • review drafts
  • saved reviews
  • saved timestamps
  • savedBy when reviews were saved
  • exportedBy when exported by a logged-in user

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Generated-only exports

If a run was exported before review, the export may show: 
saved: null
savedAt: null
savedBy: null
ratings: null
That is expected. Generated-only exports are useful for debugging Engine behavior, but reviewed exports are better for training and product decisions.

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Reviewed exports

A reviewed export is stronger because it includes human judgment. Before sending an export to product or engineering, make sure the relevant items have been saved.

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How engineers should use exports

Engineers should read exports for patterns, not isolated annoyances. A single odd response may be useful. A repeated pattern is much more important. Pattern examples:
  • disorientation prompts route to generic capability redirect
  • payment risk gets detected but next action is vague
  • Lucia sounds warm but does not narrow the field
  • Spanish prompts lose warmth
  • trust repair language overclaims

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Export testing suite data from Eval Labs

export-controls Export controls for easy usability with multiple data formats. _Example JSON code/format from exported (custom or automated) prompt suite. _ 
{
  "format": "lucia-eval-lab-session/v0.3",
  "exportedAt": "2026-04-29T19:33:10.000Z",
  "exportedBy": {
    "clerkUserId": "user_3D2BItLYUO1uqJOqzlZTvHZNgsF",
    "email": "aviv@hellolucia.ai",
    "name": "Aviv Hadar"
  },
  {
    "item_index": 0,
    "template_key": "payment-confusion",
    "category": "utility/everyday",
    "subcategory": "payments-and-settlement",
    "prompt_title": "List pending payments close to arrival",
    "prompt_text": "List pending payments close to arrival.",
    "lucia_response": "Let's start with Ava Sterling's arrival details first. 4 open tasks still need closure, and check-in is today."
  },
  {
    "item_index": 1,
    "template_key": "overwhelm-emotional-regulation",
    "category": "overwhelm/emotional regulation",
    "subcategory": "operator-nervous-system",
    "prompt_title": "I'm spinning a little",
    "prompt_text": "I'm spinning a little. Tell me what to do first so I can breathe again.",
    "lucia_response": "Take a breath. This feels heavier than it is. Nothing critical is slipping beyond the first move. I narrowed this to one first move. Begin with Ava Sterling - 4 open tasks still need closure, and check-in is today. I will keep the rest quiet and only surface what cannot wait. 9 items can stay quiet for now."
  }

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Review-layer export fields

Reviewed exports may now include: 
review_state
canon_candidate
employee_understood_need
employee_right_next_move
employee_calming_effect
employee_risk_or_confusion
employee_senior_review
employee_reusable_learning
human_what_person_is_asking_for
human_follow_through_required
human_next_step_needed
human_emotional_state
human_pressure_level
final_what_person_is_asking_for
final_follow_through_required
final_next_step_needed
final_emotional_state
final_pressure_level
final_decision_reason
final_adjudicated_at
final_adjudicator_email
Use employee fields to understand broad reviewer reaction. Use adjudication fields to understand final senior meaning. Do not treat non-adjudicated employee reaction as canonical label truth.