msio_customer_intel

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable operational context beyond those: it requires a cus_-prefixed customer_id, fetches all customer jobs and invoices, and warns that high-volume customers may cause a multi-second delay. This helps the agent set expectations and avoid surprises.

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 well-organized with labeled sections: outcome, USE WHEN, DO NOT USE WHEN, and GOTCHAS. It front-loads the core purpose, avoids repeating schema details, and every section contributes actionable information rather than filler.

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 one simple parameter, an output schema, and annotations covering safety and idempotency, the description covers the remaining needed context: what the tool returns, when to use it, when not to use it, and practical gotchas. Nothing critical is missing for correct invocation and tool selection.

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 only one parameter with no description and 0% coverage, so the description must compensate. It does by specifying that customer_id must use the cus_ prefix and is required in practice, which is the essential semantic for the single parameter. It does not go further into format details, but for a simple string ID the guidance is sufficient.

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 identifies a specific analytical tool: it computes customer intelligence as 9 binary pattern flags across churn risk, payment health, value, and service patterns, and returns only the patterns that fire with explanations. This makes its purpose concrete and distinguishes it from simple customer lookup or listing siblings like hcp_get_customer and hcp_list_customers.

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 explicit USE WHEN scenarios such as customer history review, churn risk assessment, account health checks, and pre-estimate reviews. It also gives explicit DO NOT USE WHEN guidance with named alternatives, which is the ideal tool-selection support for an agent.

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