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Hud

by io.github.pipeworx-io

Hud Income Limits

hud_income_limits
Read-onlyIdempotent

Check income eligibility thresholds (extremely low, very low, low-income) for HUD programs by area and family size. Returns income limits by category. Use to determine program qualification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoFiscal year (e.g., 2024). Omit for the most recent year.
_apiKeyYesHUD API token
entity_idNoFIPS code or metro area code for a specific area. Omit to get all areas in the state.
state_codeYesTwo-letter state code (e.g., "CA", "NY").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesIncome limits data from HUD API
yearYesFiscal year requested or 'latest'
stateYesTwo-letter state code provided in request
entity_idYesFIPS code or metro area code if provided, null otherwise

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": "Income limits data from HUD API",
+      "type": "object"
+    },
+    "entity_id": {
+      "description": "FIPS code or metro area code if provided, null otherwise",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "state": {
+      "description": "Two-letter state code provided in request",
+      "type": "string"
+    },
+    "year": {
+      "description": "Fiscal 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": "TX"
+  },
+  {
+    "_apiKey": "your-hud-api-key",
+    "entity_id": "06037",
+    "state_code": "CA",
+    "year": 2024
+  }
+]
  3. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the core behavioral traits (safe, idempotent, non-destructive) are covered. The description adds that it returns income limits by category, but no further behavioral details (e.g., rate limits, authentication needs beyond the schema). With annotations present, the description does not contradict them and provides minimal additional context, meeting the baseline.

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 description is three sentences long, front-loading the purpose and key details. It is efficient with no superfluous words. Minor improvement could be better structuring the return value mention, but overall it is concise and well-organized.

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?

Given the presence of an output schema (so return values need not be fully detailed) and annotations for safety, the description is moderately complete. It omits mention of the required API key (_apiKey) as an authentication requirement, which is important context not covered by annotations. The 'family size' inaccuracy also detracts from completeness. Still, for a straightforward query tool, it covers the essential query logic.

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

Parameters2/5

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

The input schema covers 100% of parameters with clear descriptions, so the baseline is 3. However, the description mentions 'by family size' but there is no family size parameter in the schema; this is misleading and may cause confusion about what inputs are needed. The description thus adds a negative semantic value 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 clearly states the tool's purpose: checking income eligibility thresholds for HUD programs by area and family size, and returning income limits by category. It uses specific verbs ('check', 'returns') and specifies the resource ('income eligibility thresholds'). Among sibling tools like hud_fair_market_rents, hud_chas, etc., this tool is distinctly about income limits, so it effectively differentiates itself.

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 includes 'Use to determine program qualification', giving a clear context for when to use the tool. However, it does not provide explicit when-not-to-use guidance or mention alternatives (e.g., hud_fair_market_rents for rental values). The usage context is clear but lacks exclusions.

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