Katzilla MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable behavioral context beyond annotations: it specifies the data source (HM Land Registry), update frequency (monthly), licensing (Open Government Licence), and details about the return format (Katzilla envelope with quality scores and citation data including SHA-256 hash). This significantly enhances understanding of the tool's behavior.

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?

The description is efficiently structured in two sentences: the first covers purpose, scope, and data fields; the second covers source, updates, and return format. Every element serves a clear purpose with zero wasted words, and critical information is front-loaded.

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?

Given the tool's moderate complexity, 100% schema coverage, comprehensive annotations, and existence of an output schema, the description provides excellent contextual completeness. It covers purpose, scope, data source, update frequency, licensing, and return format details—everything needed to understand the tool's value and limitations without duplicating structured field information.

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?

Schema description coverage is 100%, so the schema already fully documents all 6 parameters. The description mentions the three location parameters (postcode, town, county) and implies price filtering, but doesn't add meaningful semantic context beyond what's in the schema. This meets the baseline expectation when schema coverage is complete.

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 clearly states the tool's purpose: 'Search property transactions by postcode, town, or county' with specific data fields (sale price, property type, tenure, transaction date) and geographical scope (England and Wales). It distinguishes itself from siblings by focusing on UK housing data, unlike other tools in the list that cover different domains like agriculture, crime, or crypto.

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?

The description provides clear context for when to use this tool: for UK house price data from HM Land Registry, with monthly updates. It doesn't explicitly mention when not to use it or name specific alternatives among siblings, but the domain-specific context (housing vs. other categories) strongly implies appropriate usage scenarios.

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