Vectra AI MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns a JSON string with a list of users, which is helpful, but lacks critical details: it doesn't mention pagination behavior (despite a 'limit' parameter), authentication requirements, rate limits, or whether this is a read-only operation. For a list tool with no annotations, 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 brief and front-loaded with the core purpose in the first sentence. The second sentence clarifies the return type, which is useful. There's no wasted text, but it could be slightly more structured (e.g., bullet points for key behaviors). Overall, it's efficient but not perfectly polished.

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 (4 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema likely covers return values, so the description's mention of a JSON string is redundant. However, it lacks behavioral context (e.g., pagination, auth) and usage guidelines, making it incomplete for optimal agent understanding. It meets the bare minimum but has clear gaps.

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 fully documents all 4 parameters (role, last_login_after, email, limit) with descriptions, defaults, and constraints. The description adds no parameter-specific information beyond what's in the schema, but it does imply filtering capability through the phrase 'List users in the Vectra platform.' Baseline 3 is appropriate when the schema does the heavy lifting.

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 users in the Vectra platform.' It specifies the verb ('list') and resource ('users'), and distinguishes it from siblings like list_assignments or list_entities. However, it doesn't explicitly differentiate from other user-related tools (none exist in the sibling list), so it's not a perfect 5.

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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for filtering, or comparison to other tools in the sibling list (e.g., when to use this versus get_account_details). The agent must infer usage from the tool name alone.

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