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Hud Chas

hud_chas
Read-onlyIdempotent

Get housing affordability data by income level and family type. Returns household counts with cost burdens, overcrowding, and housing problems. Use for housing needs assessment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoData year (e.g., 2020). Omit for the most recent available.
_apiKeyYesHUD API token
entity_idNoFIPS code for a specific county or place. Omit to get state-level data.
state_codeYesTwo-letter state code (e.g., "CA", "NY").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesHousing affordability strategy data from HUD API
yearYesData year requested or 'latest'
stateYesTwo-letter state code provided in request
entity_idYesFIPS code if provided, null for state-level data

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "_apiKey": "your-hud-api-key",
      -    "state_code": "NY"
      -  },
      -  {
      -    "_apiKey": "your-hud-api-key",
      -    "entity_id": "06001",
      -    "state_code": "CA",
      -    "year": 2020
      -  }
      -]New value: +[
      +  {
      +    "state_code": "NY"
      +  },
      +  {
      +    "entity_id": "06001",
      +    "state_code": "CA",
      +    "year": 2020
      +  }
      +]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "data": {
      +      "description": "Housing affordability strategy data from HUD API",
      +      "type": "object"
      +    },
      +    "entity_id": {
      +      "description": "FIPS code if provided, null for state-level data",
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "state": {
      +      "description": "Two-letter state code provided in request",
      +      "type": "string"
      +    },
      +    "year": {
      +      "description": "Data year requested or 'latest'",
      +      "type": [
      +        "number",
      +        "string"
      +      ]
      +    }
      +  },
      +  "required": [
      +    "state",
      +    "entity_id",
      +    "year",
      +    "data"
      +  ],
      +  "type": "object"
      +}
  3. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "_apiKey": "your-hud-api-key",
      +    "state_code": "NY"
      +  },
      +  {
      +    "_apiKey": "your-hud-api-key",
      +    "entity_id": "06001",
      +    "state_code": "CA",
      +    "year": 2020
      +  }
      +]
  4. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that the tool returns household counts with cost burdens, overcrowding, and housing problems, which is useful behavioral context. It doesn't mention pagination, data vintage behavior, or what happens when entity_id is omitted, but the annotations carry the main safety burden.

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?

Two sentences with no filler. The core action and return content are front-loaded, and the use case is appended in a short second sentence. Every word earns its place.

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

Completeness3/5

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

The tool has an output schema, so return values are documented elsewhere. The description covers what the data is and a use case. However, it doesn't clarify the relationship to sibling HUD tools (e.g., hud_income_limits, hud_fair_market_rents) or mention that entity_id is optional for state-level data, which is a key usage nuance. For a data-retrieval tool with full schema coverage and an output schema, this is adequate but not complete.

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 100%, so the schema already documents all four parameters. The description adds the context that entity_id can be omitted for state-level data and year can be omitted for the most recent, but those details are already in the schema. The description's mention of 'income level and family type' maps to the data returned, not to specific parameters, so it adds minimal value beyond the schema.

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

Purpose4/5

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

The description states a specific verb ('Get'), a clear resource ('housing affordability data'), and the key dimensions ('by income level and family type'). It also lists the returned content (household counts with cost burdens, overcrowding, housing problems). It doesn't explicitly differentiate from sibling HUD tools like hud_income_limits or hud_fair_market_rents, but the resource and return content are specific enough to distinguish it.

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

Usage Guidelines3/5

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

The description says 'Use for housing needs assessment,' which gives a clear use case. However, it doesn't explicitly state when NOT to use this tool versus siblings like hud_income_limits or hud_fair_market_rents, nor does it mention alternatives. The use case is implied but not contrasted with other HUD tools.

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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