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Scored across 11 tools
Most tools map to distinct datasets (fuel, LPG, grocery, pharma, freight, tariffs, taxes, states), but the highest-level analytical tools blur badly: brazil_purchasing_power_oracle and brazil_cost_of_living both claim PPP/cost-of-living synthesis, and both duplicate thermal-parity math already owned by brazil_energy_tariffs. brazil_compare_regions also overlaps with the per-dataset price tools since they already return per-state averages. The long cross-referencing descriptions mitigate but do not eliminate the ambiguity.
All 11 names share a predictable brazil_ namespace and use snake_case, which makes the set feel like one coherent product. The deviation is stylistic: brazil_list_states and brazil_compare_regions are verb-first actions while the rest are noun-phrase resources, and 'oracle' is a vague outlier term. Minor, readable inconsistency rather than chaos.
Eleven tools is squarely in the well-scoped range for a multi-domain national price-intelligence server, and each maps to a real data source (ANP, ANEEL, CONFAZ, CMED, SEFAZ, ANTT). No filler tools and no obvious need to split or merge beyond the oracle/cost-of-living overlap.
Coverage spans fuels, LPG, grocery basket, electricity tariffs, freight, tax decomposition, pharma, state metadata, and cross-state comparison, plus higher-level cost-of-living synthesis — strong for the stated domain. The notable gap is temporal: all datasets are advertised as daily/weekly/monthly updated but no tool exposes historical series or trend deltas, and there is no station/city-level drilldown outside fuel prices.