Katzilla MCP

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the return format ('Katzilla envelope { data, quality, citation }'), describes quality metrics ('freshness/uptime/confidence'), and details citation contents ('source URL, license, SHA-256 data hash'), which aids in understanding output behavior and auditability.

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 source; the second details the return format and metadata. Every sentence adds value without redundancy, and it is front-loaded with key information. No wasted words or unnecessary elaboration.

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 complexity (3 parameters with full schema coverage, annotations covering safety/idempotency, and an output schema implied by the return format description), the description is complete. It explains the data source, update frequency, return structure, and quality metrics, compensating for any gaps. With annotations and schema handling technical details, the description provides sufficient context for effective use.

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%, with each parameter well-documented in the schema (year range, state codes, actionsTaken enum). The description mentions parameters implicitly ('by action type, year, and geography') but does not add significant semantic details beyond what the schema provides, such as explaining the significance of action types or geographic scope. Baseline 3 is appropriate given high schema coverage.

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 with specific verbs ('aggregated mortgage lending statistics') and resources ('Home Mortgage Disclosure Act data from CFPB'), distinguishing it from siblings like consumer__cfpb-complaints by focusing on mortgage data rather than complaints. It explicitly mentions the data scope ('loan originations, denials, and applications nationwide') and source details.

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 the tool ('aggregated mortgage lending statistics by action type, year, and geography'), but does not explicitly state when not to use it or name alternatives among siblings. It implies usage for HMDA data queries without contrasting with other consumer tools.

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