Vectra AI MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context beyond basic functionality: case-insensitive partial name matching, return format details (formatted string with specific fields), and handling of no matches. However, it doesn't cover critical behavioral traits like error handling, rate limits, authentication requirements, or whether this is a read-only operation (implied but not stated).

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 and front-loaded: the first sentence states the core purpose, followed by behavioral details and return format. Every sentence adds value—no redundant or wasted text. However, the structure could be slightly improved by separating behavioral notes from return specifications more clearly.

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 no annotations, no output schema, and a simple single-parameter tool, the description is moderately complete. It covers purpose, search behavior, and return format adequately. However, for a tool in a security/entity management context, it lacks details on permissions, data freshness, or error scenarios, which would enhance completeness for agent usage.

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 the parameter 'entity_name' fully documented in the schema ('Name or partial name of the entity to look up. No spaces allowed.'). The description adds minimal value beyond the schema, only reinforcing 'partial names' matching. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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: 'Retrieve information about an entity (account or host) by its name' with specific verbs ('Retrieve information') and resources ('entity'). It distinguishes from siblings like 'get_account_details' or 'get_host_details' by focusing on name-based lookup rather than ID-based or other criteria. However, it doesn't explicitly contrast with 'lookup_host_by_ip' (IP-based lookup) or 'list_entities' (bulk listing), leaving some sibling differentiation incomplete.

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 implies usage context through 'Search is case-insensitive and can match partial names' and the return behavior, suggesting it's for fuzzy name matching. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_account_details' (for specific accounts by ID) or 'lookup_host_by_ip' (for IP-based lookups). No when-not-to-use or prerequisite information is provided.

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