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. It states the tool returns 'full details' and a JSON string, which is helpful, but lacks critical behavioral context: it doesn't mention whether this is a read-only operation, if there are rate limits, pagination behavior, or what 'full details' entails compared to other tools. The description adds some value but leaves significant gaps for a tool with no annotation coverage.

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 concise with two sentences: one stating the purpose and one describing the return value. It's front-loaded with the core functionality. However, the second sentence could be omitted since an output schema exists, making it slightly redundant.

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 that an output schema exists (so return values are documented elsewhere) and schema coverage is 100%, the description is minimally adequate. However, for a tool with no annotations and multiple sibling tools offering similar functionality, it should provide more context on differentiation and behavioral traits to be fully complete.

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 already fully documents both parameters (entity_id and state). The description adds no additional parameter semantics beyond what's in the schema, such as explaining what an 'entity' represents or the implications of different states. Baseline 3 is appropriate when the schema does all the work.

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 verb ('List') and resource ('all detections with full details for a specific entity'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_detection_ids' or 'list_detections_with_basic_info', which offer similar listing functionality but with different detail levels.

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 like 'list_detection_ids' (which might list IDs only) or 'list_detections_with_basic_info' (which might provide less detail). It mentions filtering by entity and state but doesn't explain why one would choose this over other detection-listing tools.

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