tasks/task_028_comprehensive_decision_medium_medium003.md

---
id: task_028_comprehensive_decision_medium_medium003
name: comprehensive_decision-medium-medium003
category: comprehensive_decision
grading_type: llm_judge
timeout_seconds: 1200
gold_file: qa_gold/comprehensive_decision/medium003.json
workspace_files: [
  {
    "source": "database/bilingual_translation_english_chinese.json",
    "dest": "database/bilingual_translation_english_chinese.json"
  },
  {
    "source": "database/enterprise/company_core.csv",
    "dest": "database/enterprise/company_core.csv"
  },
  {
    "source": "database/enterprise/company_operation_status.csv",
    "dest": "database/enterprise/company_operation_status.csv"
  },
  {
    "source": "database/enterprise/company_operation_status_detail.csv",
    "dest": "database/enterprise/company_operation_status_detail.csv"
  },
  {
    "source": "database/enterprise/company_operation_yearly_status.csv",
    "dest": "database/enterprise/company_operation_yearly_status.csv"
  },
  {
    "source": "database/enterprise/company_profile.csv",
    "dest": "database/enterprise/company_profile.csv"
  },
  {
    "source": "database/enterprise/company_profile_as.csv",
    "dest": "database/enterprise/company_profile_as.csv"
  },
  {
    "source": "database/enterprise/company_profile_eu.csv",
    "dest": "database/enterprise/company_profile_eu.csv"
  },
  {
    "source": "database/enterprise/company_profile_na.csv",
    "dest": "database/enterprise/company_profile_na.csv"
  },
  {
    "source": "database/enterprise/company_profile_oc.csv",
    "dest": "database/enterprise/company_profile_oc.csv"
  },
  {
    "source": "database/industry/national_industry_status.csv",
    "dest": "database/industry/national_industry_status.csv"
  },
  {
    "source": "database/industry/national_industry_status_detail.csv",
    "dest": "database/industry/national_industry_status_detail.csv"
  },
  {
    "source": "database/industry/national_industry_yearly_status.csv",
    "dest": "database/industry/national_industry_yearly_status.csv"
  },
  {
    "source": "database/industry/regional_industry_status.csv",
    "dest": "database/industry/regional_industry_status.csv"
  },
  {
    "source": "database/industry/regional_industry_status_detail.csv",
    "dest": "database/industry/regional_industry_status_detail.csv"
  },
  {
    "source": "database/industry/regional_industry_yearly_status.csv",
    "dest": "database/industry/regional_industry_yearly_status.csv"
  },
  {
    "source": "database/internal_metrics.csv",
    "dest": "database/internal_metrics.csv"
  },
  {
    "source": "database/policy/policy_release_status.csv",
    "dest": "database/policy/policy_release_status.csv"
  },
  {
    "source": "database/policy/policy_resource.csv",
    "dest": "database/policy/policy_resource.csv"
  }
]
---

## Prompt

In 2022, measuring per capita output efficiency of automobile manufacturing by province using revenue per capita (total operating revenue ÷ total employee count), among all provinces nationwide, what is the specific value in yuan per person for the province with the highest indicator? Compared to the national average, by what percentage (1 decimal place) is that province's per capita revenue higher?

Output guidelines:
Two answers required: first is a numeric value (2 decimal places), unit yuan/person; second is a percentage (1 decimal place), unit %. If relevant data cannot be found, respond with "No relevant data found".

Only use files under `./database/`.

## Expected Behavior

Agent should read the provided `database/` files, compute the result, and return the final answer. The final answer must follow the required output format.

## Grading Criteria

- [ ] Final answer semantically matches the gold `answer`.
- [ ] Output format follows `guidelines`.

## LLM Judge Rubric

### Criterion 1: Multi-answer Correctness (Weight: 100%)

Gold answer JSON:
`[3898878.23, 175.0]`

Scoring rules:
- The gold answer is a list with N=2 parts.
- Judge each predicted part against the corresponding gold part by semantic equivalence.
- Return `scores` with `part_0 ... part_1` each as 0 or 1.
- Return `total = (sum(part_i)) / 2` exactly.
- If the model output is missing or cannot be parsed into 2 comparable parts, score all parts 0.