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Hud

by io.github.pipeworx-io

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. Dates show when Glama detected each change.

  1. 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"
+}
  2. 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
+  }
+]
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and idempotency. The description adds behavioral context by specifying that the tool returns 'household counts with cost burdens, overcrowding, and housing problems', which is not in annotations.

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

Conciseness5/5

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

The description is extremely concise, using three short sentences that front-load the action and resource. Every sentence adds value without redundancy, making it easy to parse quickly.

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?

Given the complexity of 4 parameters and the presence of an output schema and rich annotations, the description is complete enough. It clarifies the tool's purpose and output, though it omits details like pagination or authentication requirements (already in schema).

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?

The input schema has 100% description coverage for all 4 parameters. The description does not add any additional meaning beyond what the schema already provides, so 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 clearly states the action 'Get', the resource 'housing affordability data', and specifies the dimensions 'by income level and family type'. It lists the returned data types and suggests a use case, making the purpose unmistakable.

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 explicitly says 'Use for housing needs assessment', providing a clear usage context. However, it does not mention when not to use or contrast with sibling tools, so it lacks exclusion guidance.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but several query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile, compare_entities, validate_claim) overlap in functionality, which could confuse an agent. The Polymarket and HUD subgroups are well-separated.

Naming Consistency3/5

Tool names use multiple styles: verb_noun (ask_pipeworx), prefixed groups (hud_*, polymarket_*, pipeworx_*), and standalone verbs (forget, recall). While subgroups are consistent, the overall set lacks a uniform pattern.

Tool Count3/5

With 35 tools, the server offers broad data and analytics capabilities. The count is on the high side but justified by the range of features (HUD, general queries, prediction markets, memory, subscriptions). Some tools are highly specialized.

Completeness4/5

The tool surface covers housing data, multi-source querying, prediction markets, memory, subscriptions, and meta-tools. Minor gaps exist (e.g., deeper user account management), but core workflows are well-supported.

Resources