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

The annotations already indicate a read-only, idempotent, non-destructive operation, and the description adds meaningful behavioral detail: it returns the kind of source system, explains limitations such as lacking support for aggregation, and states that hosts, credentials, table names, and connection strings are never included. It also notes that access requires a data owner's approval, which goes beyond the structured metadata.

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 organized with clear conditional paragraphs for the two invocation modes. Every sentence contributes either core behavior, usage guidance, or a security boundary, and the most important information comes first.

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?

There is no output schema, so the description carries the burden of describing return contents. It specifies list results, product schema details, field sensitivity, glossary information, system kind limitations, and information that will never be exposed. This is enough for an agent to invoke the tool confidently and to decide when to follow up with request_access.

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?

Both parameters are fully documented in the schema, so the baseline is high. The description adds real value by explaining exactly what happens when `dataProduct` is omitted versus provided, and why the returned information matters before requesting access. This goes beyond the schema's basic variable slUg description and clarifies what the caller should do with the parameter.

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 names the resource, governed data products, and distinguishes two modes: listing all products when `dataProduct` is omitted, and describing a single product's schema when it is supplied. It also references the access-request flow, so the tool's role is clear relative to its sibling tool.

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?

It explicitly explains when to omit `dataProduct`, when to supply it, and instructs the agent to read this description before requesting access. It names the alternative action, springroll.connect.request_access, making the decision boundary between describing data and requesting access explicit.

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