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"task_id": "objective_easy_01",
"version": "2.0.0",
"created_at": "2026-03-12",
"metadata": {
"domain": "credit_card_optimization",
"difficulty": "easy",
"task_number": 1,
"complexity_hint": {
"max_tokens": 4000,
"expected_output": "single card recommendation with EV calculation"
},
"requires_human_review": false
},
"prompt": {
"system": "",
"user": "You are a financial advisor. Recommend the single best credit card for this user and calculate the expected value over 12 months.\n\nUser profile:\n- Monthly spending: $600 dining, $500 groceries, $200 travel, $400 flights, $300 hotels, $150 gas, $60 streaming, $100 transit, $800 everything else\n- Takes 8 trips per year (values lounge access at $30/visit)\n- Uses Uber regularly\n- Uses streaming services\n- Dines at Resy restaurants\n- Has Global Entry\n- No existing credit cards\n- Time horizon: 12 months\n\nProvide a detailed EV breakdown showing signup bonus value, ongoing rewards, credits, perks, and annual fees. Use the point valuations from the knowledge base.",
"knowledge_base_ref": "knowledge_base.md",
"kb_filter": [
"American Express Gold",
"Chase Sapphire Preferred",
"Chase Sapphire Reserve",
"Capital One Venture X",
"Citi Strata Premier"
],
"system_prompt_ref": "system_prompt_template.md"
},
"scoring": {
"dimensions": {
"card_selection": {
"weight": 0.25,
"type": "automated",
"description": "F1 of recommended cards vs. optimal set",
"checks": {
"expected_cards": [
"American Express Gold"
]
},
"hard_constraint": false
},
"ev_accuracy": {
"weight": 0.3,
"type": "automated",
"description": "EV accuracy vs. computed ground truth from card database",
"reference": {
"user_profile": {
"monthly_spend": {
"dining": 600,
"groceries": 500,
"travel": 200,
"flights": 400,
"hotels": 300,
"gas": 150,
"streaming": 60,
"transit": 100,
"everything_else": 800
},
"lounge_visits_per_year": 8,
"uses_uber": true,
"uses_streaming": true,
"uses_resy_restaurants": true,
"has_global_entry": true,
"time_horizon_months": 12
},
"expected_card_ids": [
"american_express_gold"
],
"ev_tolerance_pct": 0.05
}
},
"factual_fidelity": {
"weight": 0.3,
"type": "automated",
"description": "Accuracy of factual claims about cards (earning rates, fees, credits, bonuses)",
"reference": {
"extracted_claims": null,
"reference_ev_usd": null
}
},
"constraint_compliance": {
"weight": 0.15,
"type": "automated",
"description": "Did the agent respect user constraints and issuer rules",
"checks": {
"expected_cards": [
"American Express Gold"
],
"expected_housing_option": null
},
"hard_constraint": false
}
},
"passing_threshold": 0.6,
"hard_constraint_failure_zeroes_dimension": true
},
"reference_solution": {
"_status": "COMPUTED",
"recommended_cards": [
"American Express Gold"
],
"total_ev_usd": null,
"ev_breakdown": null,
"housing_option": null,
"key_constraints_flags": [],
"expert_notes": "Ground truth EV is computed from card_database.json + user_profile at evaluation time. No expert override needed."
}
}
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