Get a read-only market screen for a metro or state: latest Zillow typical home value (ZHVI) and asking rent (ZORI), with 1-year and 5-year changes where available. Returns market context only, not a parcel record, comparable sale, owner/title result, appraisal, score, or investment decision.
| Name | Required | Description | Default |
|---|---|---|---|
| region | Yes | Metro or state name (e.g. 'Austin, TX', 'Houston', 'Texas') or a Zillow region id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already supply readOnlyHint, idempotentHint, and destructiveHint=false, and the description reinforces and adds context: it returns only market context, and historical changes are included only 'where available.' No contradiction with the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly written sentences: the first delivers the operation, scope, and data payload; the second delivers a compact exclusion list that prevents misuse. There is no filler or redundant elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter, read-only tool with safety covered by annotations, the description explains the input scope, the exact returned metrics, the availability caveat, and what type of answer this is not. That is sufficient for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema documents the sole parameter completely, including allowed forms ('Austin, TX', 'Houston', 'Texas') and Zillow region id. The description's 'metro or state' phrasing adds no semantic value beyond the schema, so the high-coverage baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get a read-only market screen for a metro or state,' then names the exact metrics returned (ZHVI, ZORI, 1/5-year changes). The exclusion list ('not a parcel record, comparable sale, owner/title result, appraisal, score, or investment decision') clearly separates it from the many property/real-estate siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the appropriate scope (metro/state market context) and gives explicit when-not guidance by listing what the tool does not return. It does not name the specific sibling tools to use for parcel, comparable, or appraisal needs, which would make the routing guidance fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.
Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.
294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.
The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.