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Explain a mortgage specialty

explain_specialty
Read-onlyIdempotent

Use this when someone asks what a mortgage loan type or borrower situation means, such as a DSCR loan, a bank statement loan, an ITIN loan, a non-warrantable condo or an FHA loan. Returns, for one specialty slug, what it is, why it can be hard to get done, the questions a borrower should ask a loan officer about it, its synonyms and a canonical_url.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesOne of: condo, condo-non-warrantable, co-op, multi-family-2-4, manufactured, rural, new-construction, mixed-use, condotel, vacation-home, fha, va, usda, jumbo, non-qm, dscr, bank-statement, reverse, renovation, construction, heloc, down-payment-assistance, crypto-mortgage, self-employed, first-time-buyer, investor, refinance, permanent-resident, foreign-national, itin, low-credit, recent-credit-event, physician, 1099-income, asset-based

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
labelYes
api_urlYes
categoryYes
why_hardYes
descriptionYes
canonical_urlYes
questions_to_askYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered by structured data. The description's statement of returned content (what it is, why it is hard, questions to ask, synonyms, canonical_url) is largely redundant with the output schema. It adds no rate limits, auth requirements, or failure behavior, so a 3 is fair.

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?

Two sentences, front-loaded with the trigger condition before the return description, and zero filler. Every clause carries information the agent can act on.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter lookup with a fully described schema, complete annotations, and an existing output schema, the definition supplies everything needed: when to invoke it, what the slug represents, and that it is scoped to one specialty at a time. Nothing material 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% and the slug parameter already carries the full enumerated vocabulary, so the schema does the heavy lifting. The description's examples of natural-language surface forms ('a DSCR loan', 'an ITIN loan') add mild value in mapping user phrasing to the slug, but no syntax, format, or edge-case guidance beyond that. 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?

States a specific verb (explain) and resource (a mortgage specialty), and enumerates concrete surface forms (DSCR loan, bank statement loan, ITIN loan, non-warrantable condo, FHA loan) so the agent knows exactly what domain this covers. It is clearly distinguishable from list_specialties (enumeration) and the get_* sibling tools (entity lookup).

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?

Gives an explicit trigger: 'Use this when someone asks what a mortgage loan type or borrower situation means.' That is clear when-to-use context, and the examples reinforce it. It does not name an alternative or a when-not condition (e.g., use list_specialties to discover valid slugs), so it stops short of full routing 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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