cerebrochain-mcp-server

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

No annotations are provided, so the description carries full disclosure burden. It successfully notes the API key requirement and the 90-day time constraint, but omits other behavioral traits like pagination, rate limits, or data freshness/caching 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?

Single efficient sentence using an em-dash to append details without repetition. Information is front-loaded ('Get shipment history with analytics') and every clause adds value (scope, data types, auth requirement).

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?

While no output schema exists, the description compensates by enumerating the returned data categories (delivery rates, carrier performance, shipment history). It appropriately covers the content for a zero-parameter analytics tool, though it could specify the response format (e.g., JSON array vs summary object).

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?

Input schema contains zero parameters, which establishes a baseline score of 4. The description correctly implies no filtering parameters are available by stating 'all shipments' and '90-day view' as fixed scope.

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?

Description clearly states the tool retrieves 'shipment history with analytics' and specifies the exact scope (90-day view) and data categories returned (delivery rates, carrier performance). This effectively distinguishes it from siblings like track_shipment (individual tracking) and list_orders (different domain).

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 '90-day view' and 'analytics' phrasing implies this is for historical reporting rather than real-time operations, but there is no explicit guidance on when to use this versus track_shipment for specific shipment tracking or list_orders for order-based queries.

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