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unit-commitment-data-modeling

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Use for parsing structured unit commitment input data from JSON, CSV, benchmark cases, spreadsheets, databases, or nested tables; finding fields for time periods, resources, load, reserve, generator limits, initial conditions, startup data, renewable availability, and production costs without assuming one source-specific schema.

tasks/energy-unit-commitment/environment/skills/unit-commitment-data-modeling/SKILL.md

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# Unit Commitment Structured Data Parsing

Use this skill when a unit commitment task provides structured data and you need to map fields into UC concepts. The source may be JSON, CSV, spreadsheets, database tables, or nested dictionaries. The prompt and schema are the source of truth; do not assume one benchmark or package.

## Parsing Workflow

1. Load data with structured parsers: JSON as objects, CSV/sheets as tables, databases as query results.
2. Inspect schema: top-level keys, tables/sheets, resource groups, time-series fields, cost curves, startup tiers, and initial-condition fields.
3. Identify the time axis: number of periods, labels, duration, and report convention.
4. Identify resource sets: thermal, renewable, storage, imports, zones, reserve products, or network objects.
5. Normalize fields into arrays/tables with explicit shapes.
6. Preserve original names and source ordering for final reports.
7. Run parser-level checks before modeling.
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