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Baneado98

muni-dev-cost

summarize_by_state

Aggregate municipal development costs by US state to identify cheap or expensive building markets. Compare total or water-sewer costs across states with national benchmarks.

Instructions

Roll the entire covered dataset up to the STATE tier: for every US state we hold real city schedules in, get the number of cities covered, the min / median / max municipal development cost across them, the cheapest and priciest city, and which fee categories the state's cities assess. Plus a national roll-up (cheapest / priciest city anywhere, national median). This is the state-level site-selection map a developer scans before drilling into cities — 'which states are cheap or expensive to build in, and how many of my candidate markets do you actually cover?'. Rank on water+sewer only or on the GRAND TOTAL across every fee category. Computable only over the full normalized cross-jurisdiction dataset, and it sharpens as coverage grows. Optionally pass 'basis' ('total' default, or 'water_sewer'), 'dev_type', 'meter_size'. PREMIUM: pay per call with x402 (USDC on Base) or set a prepaid key (MUNI_DEV_COST_KEY).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
basisNo'total' (grand total across all fee categories, default) or 'water_sewer' (water+sewer only).
dev_typeNoDevelopment type (default single_family).
meter_sizeNoWater meter size for per-meter-table jurisdictions (default 5/8").
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses the premium payment model and that results sharpen as coverage grows. Could explicitly state it's read-only, but overall transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one long paragraph that front-loads the purpose but includes premium payment details which could be separate. It's adequately sized but slightly wordy for the information conveyed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Comprehensive in explaining outputs (number of cities, costs, fee categories) and use case. No output schema, but description fully covers what user gets. Good given many sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. Description adds meaning by defining default values for basis, dev_type, meter_size and explaining options like 'total' vs 'water_sewer'. This goes beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it rolls up the dataset to the STATE tier and lists specific outputs (cities covered, costs, fee categories). It distinguishes from siblings like rank_jurisdictions_by_cost which operate at jurisdiction level.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains this is for high-level state site-selection before drilling into cities, and that it works on the full dataset. It doesn't explicitly list when not to use but provides clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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