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Landlord Lookout: Making Tax Digital

Look up one MTD software product

get_mtd_software_product
Read-onlyIdempotent

Facts about one product on HMRC's list of Making Tax Digital for Income Tax software, by name: price, free plan, income types, whether it files the year-end tax return, VAT, Welsh, where it runs, its HMRC listing, the vendor's website and a link to Landlord Lookout. If several products match, returns their names to choose from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesProduct or vendor name, such as "FreeAgent" or "Landlord Vision".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real behavior: the fuzzy-match fallback ('if several products match, returns their names to choose from'), which an agent needs to handle the response correctly.

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?

Two sentences, front-loaded with the resource and its field coverage. The long field list earns its place because there is no output schema, though it reads as a run-on enumeration rather than being structured.

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?

With no output schema, the description compensates by enumerating the returned fields (price, free plan, income types, year-end filing, VAT, Welsh, platforms, HMRC listing, vendor site, link). Combined with the multi-match behavior, an agent has everything needed to call and interpret this tool.

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% for the single 'name' parameter, including examples, so the schema does the heavy lifting and the baseline is 3. The description adds only the soft hint that matching may be non-exact via the multi-match clause.

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?

States a specific verb (look up facts about one product) and resource (HMRC MTD for Income Tax software list), and the field enumeration makes the scope concrete. It implicitly separates itself from find_mtd_software via 'by name' and 'one product', but never names the sibling or states the distinction explicitly.

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?

Usage is implied: you already have a product or vendor name and want that one product's details. There is no explicit when-to-use/when-not, and no pointer to find_mtd_software for the discovery case, which is the natural alternative.

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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