Three tools with identical parameter schemas and minimal descriptions. All tools have proper naming (verb_noun pattern: get_*) and valid JSON Schema with type constraints (regex patterns, enums). However, descriptions are extremely terse (10-40 chars, well below the 50-200 char baseline for LLM optimization). Parameter descriptions are generic ('Specify the X (optional)') and lack context about what data is returned or when to use each tool. No output schema documentation visible. Error handling returns plain text without recovery guidance. Tools lack differentiation in their descriptions despite querying different energy data sources.

• Expand tool descriptions to 80-150 chars. Example: 'Get energy consumption data for Portugal. Filter by day (01-31), month (01-12), year (YYYY), or time (HH:MM). Returns consumption totals sorted by date or value. Use this to analyze historical consumption trends.'
• Add explicit parameter descriptions with format and range. Example for 'day': 'Day of month (01-31). If omitted, returns data for all days in the specified month or year.'
• Document the output schema in the tool description or as a separate field. Example: 'Returns array of {date: string, consumption_mwh: number, source: string}.'
• Enhance error responses with recovery guidance. Example: 'Failed to retrieve energy consumption data. Verify date parameters are valid (day 01-31, month 01-12, year YYYY). Retry with a shorter date range.'
• Differentiate tool descriptions to clarify use cases. Example: 'get_energy_consumption: Retrieve electricity consumed by end users. get_national_produced_energy: Retrieve total electricity generated nationally. get_energy_injected: Retrieve electricity injected into distribution networks by producers.'