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by io.github.TigerManOnFire
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Rank the areas of a state or district

footprint_top_areas
Read-onlyIdempotent

List the top ~0.7 sq km areas in an Indian state or district, ranked by building growth, building count, height or price outlook.

Use for "where is building fastest in Karnataka", "fastest-growing areas near Pune", "tallest neighbourhoods in Goa". Only areas with enough buildings to measure are ranked, one row per village or locality. Each row gives the place, its nearest town, the ranked figure, the share of ground built on five years ago and now, building count, a price where one is published, and coordinates for footprint_get_area. A ranking, not advice.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "region": "<region>"
    },
    "name": "footprint_top_areas"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many areas to return.
regionYesAn Indian state, union territory or district, e.g. 'Karnataka', 'Goa', 'Pune'.
sorted_byNobuilding_growth: fastest built-area growth over 5 years (the default and the most informative). most_buildings: building count. tallest: average building height. price_outlook: forecast price growth (mostly follows the city trend, so areas in one city tie).building_growth

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower; the description still adds meaningful behavior — only areas with enough buildings are ranked, one row per village or locality, and the row payload is enumerated. It also flags that price_outlook mostly follows the city trend, which warns of degenerate ties.

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

Conciseness4/5

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

The first sentence front-loads the verb, scope and ranking dimensions, with usage examples and row contents following logically. Some quoted example phrasing is slightly padded, but nothing is genuinely redundant.

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

Completeness4/5

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

With no output schema, the description usefully enumerates the returned fields (place, nearest town, ranked figure, built share past/now, building count, price, coordinates) and explains ranking eligibility. It leaves minor gaps such as behavior for an unrecognized region or a region with too few areas to fill the limit.

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

Parameters3/5

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

Schema coverage is 100%, so region, limit and the sorted_by enum are already fully documented, including the note that building_growth is the most informative and price_outlook tends to tie. The description only restates the four ranking modes, adding no syntax or format detail beyond the 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 states a specific verb (rank/list) and resource (top ~0.7 sq km areas in an Indian state or district) plus the four ranking modes. It is clearly distinguishable from siblings, and it even points to footprint_get_area for per-area detail.

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?

Quoted example questions ('where is building fastest in Karnataka', 'tallest neighbourhoods in Goa') give concrete usage context, and the caveat 'A ranking, not advice' plus the minimum-buildings requirement set expectations. It stops short of explicitly saying when to prefer footprint_compare_areas or footprint_search_places instead.

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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