Vultr MCP

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

No annotations are provided, so the description carries full burden. It states this is a 'List' operation, implying it's read-only and non-destructive, but doesn't disclose any behavioral traits like pagination, rate limits, authentication requirements, error conditions, or what 'List of Kafka topics' entails (e.g., format, fields). For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 appropriately sized with three sentences: a purpose statement, parameter documentation, and return value note. It's front-loaded with the core purpose. However, the 'Args' and 'Returns' sections use a non-standard format that might be less structured than ideal, and the return note is vague ('List of Kafka topics').

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 context: 1 parameter with 0% schema coverage, no annotations, no output schema, and no sibling differentiation, the description is incomplete. It covers the parameter semantics adequately but lacks behavioral details (e.g., pagination, error handling), usage context vs. siblings, and specifics on the return value. For a tool in a complex environment with many siblings, more guidance is needed.

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?

The description includes an 'Args' section that documents the single parameter 'database_id' as 'The Kafka database ID or label', adding semantic meaning beyond the schema (which has 0% description coverage). This compensates partially for the low schema coverage. However, it doesn't elaborate on format examples, validation rules, or how 'label' differs from 'ID', leaving some ambiguity.

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: 'List Kafka topics' with the specific resource 'Kafka databases only'. It uses a specific verb ('List') and identifies the resource type. However, it doesn't differentiate from potential siblings like 'get_kafka_topic' (which appears to fetch a single topic) or 'list_databases' (which might list databases rather than topics).

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 minimal guidance: it specifies 'Kafka databases only', which implies this tool is for Kafka-specific resources. However, it offers no explicit guidance on when to use this versus alternatives like 'get_kafka_topic' (for single topic details) or 'list_databases' (for listing databases themselves). There's no mention of prerequisites, exclusions, or comparison with sibling tools.

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