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Safe Rate

Research a mortgage lender

research_lender
Read-onlyIdempotent

Look up any US mortgage lender by name or NMLS ID: origination volume, approval and pull-through rates, product mix and geographic footprint, from federal HMDA data.

Input Schema

NameRequiredDescriptionDefault
lenderYesLender name or NMLS ID, e.g. "Rocket Mortgage" or "3030".
geographyNoOptional two-letter state code to narrow the metrics, e.g. "IL".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered without help from the text. The description contributes useful behavioral context by disclosing the HMDA provenance of the data. It does not mention data recency/lag, which matters for HMDA-sourced figures.

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?

A single well-formed sentence with the resource and identifier first and the metrics and data source following. Every clause carries information, though the metric list is dense and slightly long for one sentence.

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?

With only two parameters, no output schema, and full annotation coverage, the description needs to convey what comes back, and it does by enumerating the metric categories. Only the staleness of HMDA data and the effect of the geography filter are left unspecified, which are minor gaps.

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 both parameters are already documented in the schema, making 3 the baseline. The description restates the name/NMLS ID input but never explains that the optional geography parameter narrows metrics to a state; the phrase "geographic footprint" refers to a returned metric, not the input, so it adds no meaning 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 names a specific verb and resource ("Look up any US mortgage lender") and enumerates the returned metrics: origination volume, approval and pull-through rates, product mix, and geographic footprint. It also states the data source (federal HMDA). It stops short of explicitly distinguishing itself from the sibling find_lenders_in_market, which is a market-discovery tool rather than a single-lender lookup.

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 tells the agent which identifier forms are accepted (lender name or NMLS ID), which implies usage context, but it never says when to prefer this over find_lenders_in_market or get_market_context, and gives no exclusions or prerequisites. Usage guidance is implied rather than stated.

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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