Skip to main content
Glama

Lotlytics — US Real Estate Market Data & Investment Analytics

Investment health score (1-10)

get_market_health
Read-onlyIdempotent

Investment health score (1-10) for a US market, with a label (Strong Buy / Favorable / Neutral / Caution / Avoid) and the signals behind it. Example: city='Tampa', state='FL'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity or metro, e.g. 'Tampa'. Case-insensitive.
stateYesUS state, 2-letter or full, e.g. 'FL'. Required — city names repeat.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / city / description
      Previous value: -"City or metro name, e.g. 'Tampa'. Case-insensitive."New value: +"City or metro, e.g. 'Tampa'. Case-insensitive."
    • changedInput schema / properties / state / description
      Previous value: -"US state, 2-letter or full name, e.g. 'FL'. Required — city names repeat across states."New value: +"US state, 2-letter or full, e.g. 'FL'. Required — city names repeat."
  2. Changed2 schema fields changed
    • changedInput schema / properties / city / description
      Previous value: -"City or metro name, e.g. \"Tampa\", \"Kansas City\". Case-insensitive; spaces are fine."New value: +"City or metro name, e.g. 'Tampa'. Case-insensitive."
    • changedInput schema / properties / state / description
      Previous value: -"US state as a 2-letter abbreviation or full name, e.g. \"FL\" or \"Florida\". Required — city names are not unique across states."New value: +"US state, 2-letter or full name, e.g. 'FL'. Required — city names repeat across states."
  3. Changed2 schema fields changed
    • addedInput schema / properties / city / description
      Added value: +"City or metro name, e.g. \"Tampa\", \"Kansas City\". Case-insensitive; spaces are fine."
    • addedInput schema / properties / state / description
      Added value: +"US state as a 2-letter abbreviation or full name, e.g. \"FL\" or \"Florida\". Required — city names are not unique across states."
  4. First observed

TDQS

A3.6/5.0
Behavior4/5

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

The annotations already declare this as read-only, idempotent, and non-destructive. The description adds useful behavior beyond annotations by explaining that the result includes a score, a label, and the signals driving the assessment, and that it is scoped to US markets. No contradictions with annotations exist.

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 compact and front-loaded: it states the output type, label options, and underlying signals in the first sentence, and the example adds concrete input guidance. There is no redundant or filler content.

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?

For a read-only, two-parameter tool with a full input schema and an output schema, the description provides enough context to understand the purpose and expected invocation. It would be more complete if it noted when to prefer this tool over the sibling market tools, but nothing critical for calling it is missing.

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 coverage is 100%, with both city and state already well described including case-insensitivity and the need for state due to repeating city names. The description's Tampa/FL example is consistent but does not add substantive parameter semantics beyond what the schema already provides.

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 clearly states that the tool returns a 1-10 investment health score with a label and supporting signals for a US market. It is specific about the resource and output, but it does not explicitly differentiate itself from sibling tools like get_market_summary or compare_markets.

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

Usage Guidelines2/5

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

The description gives an example of city and state inputs but provides no guidance on when to use this tool versus its siblings. There is no mention of alternatives, exclusions, or conditions that would help an agent decide between get_market_health and the other market-related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.