Katzilla MCP

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

The 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 (data.gouv.fr), update frequency (daily), license information (Licence Ouverte / Open Licence 2.0), and details about the return structure (Katzilla envelope with quality scores and citation data).

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 with zero wasted sentences. It front-loads the core purpose, provides essential context about the data source and scope, and concludes with important behavioral details about returns. Every sentence serves a clear purpose.

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 search functionality, comprehensive annotations (including readOnlyHint, idempotentHint, openWorldHint), 100% schema coverage, and the presence of an output schema, the description provides complete contextual information. It covers the data source, scope, update frequency, licensing, and return structure, making it fully adequate for agent understanding.

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?

With 100% schema description coverage, the input schema already fully documents all three parameters (query, organization, limit). The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline expectation without providing extra semantic value.

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 explicitly states the action ('Search'), the target resource ('French government open data portal'), and the scope ('Over 45,000 datasets from French national and local government agencies'). It clearly distinguishes this from sibling tools by specifying the French government data source, unlike other government data tools like 'government__data-australia' or 'government__data-uk'.

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 about when to use this tool: for searching French government open data across multiple domains (demographics, transport, environment, health). It doesn't explicitly state when not to use it or name specific alternatives, but the context is sufficient to guide usage decisions.

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