Sentinel Solutions 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 mentions validation and extraction but doesn't describe what happens during validation (e.g., error handling, success criteria), what 'extract tables' entails (e.g., format, scope), or any side effects like rate limits or permissions needed. This leaves significant gaps in understanding the tool's 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 extremely concise—a single sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it efficient for an agent to parse.

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 complexity of validation and extraction tasks, the description is incomplete. With no annotations and no output schema, it fails to explain what the tool returns (e.g., validation results, extracted table data) or any behavioral nuances. This makes it inadequate for an agent to fully understand how to use the tool effectively.

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 input schema has 0 parameters, so there's no need for parameter documentation. The description doesn't add parameter information, but with no parameters to document, this is acceptable. A baseline of 4 is appropriate since the schema fully covers the (non-existent) parameters.

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 with specific verbs ('validate' and 'extract') and resource ('connector JSON definition'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_connector_tables' or 'list_data_connectors', which prevents a perfect score.

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 'get_connector_tables' or 'list_data_connectors', nor does it mention any prerequisites or context for validation. This lack of usage context leaves the agent to infer when this tool is appropriate.

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