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Find high rent-burden tracts

find_high_housing_burden_tracts
Read-onlyIdempotent

Find census tracts where veterans face the highest housing costs, for housing-aid planning and HUD-VASH/SSVF outreach. Joins ACS rent-burden data with veteran counts. Returns tracts ranked by share of renter households paying 30%+ (or 50%+) of income on rent, with FIPS location codes, veteran density, and existing-resource counts. Useful for grant proposals that cite tract-level rent burden.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
stateNo2-letter state code to filter (e.g. TX, CA)
measureNoburden = 30%+ of income on rent; severe = 50%+ (HUD definitions)severe
min_veteransNoMinimum veteran count to include tract

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real value by disclosing the data sources (ACS rent-burden joined with veteran counts) and the returned payload structure (FIPS codes, veteran density, resource counts). It omits any note on ranking/tie-break behavior or rate/auth considerations.

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?

Three sentences, front-loaded with the core purpose (finding tracts), then data provenance, then the use cases. Slightly dense in the middle sentence but no filler or repetition.

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 documents the shape of returned results and the join behind the ranking, which is what an agent needs to decide and interpret. It leaves the limit/pagination semantics and ranking tie-breaks unaddressed for a 4-parameter query tool.

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 description coverage is 75%, so the schema already documents state, measure, and min_veterans. The description restates the burden/severe 30%/50% threshold distinction, which duplicates the enum description rather than adding new meaning, and says nothing about limit or its max of 100. Baseline 3 is appropriate.

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 and resource (find census tracts) and a specific scope (veterans facing high housing costs), plus the underlying data join (ACS rent-burden data with veteran counts). It clearly differentiates from siblings like get_tract_demographics and get_housing_context by naming the rent-burden ranking and veteran focus.

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?

It gives concrete when-to-use contexts: housing-aid planning, HUD-VASH/SSVF outreach, and grant proposals citing tract-level rent burden. However, it names no alternative sibling tool or any exclusion condition (e.g., when to prefer get_housing_context or get_tract_demographics 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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