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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds value by specifying the return format (SDMX 2.1 structure XML), the agency scope (BBK), and the behavior when flowRef is provided. This goes beyond what annotations convey.

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 three sentences, front-loaded with the primary purpose, and each sentence provides distinct value: what the tool lists, the output format and scope, and how to narrow the result. No wasted words or repetition.

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?

For a read-only listing tool with one optional parameter and no output schema, the description covers the output type, the list scope (all under BBK), the meaning of a dataflow, common identifiers, and the effect of the flowRef parameter. This is sufficiently complete for an agent 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?

Schema coverage is 100% for the single parameter flowRef, with a clear description in the schema. The tool description adds extra nuance: 'includes its DataStructure reference' when a flowRef is passed, which is not stated in the schema. This meaningful addition justifies a score above baseline.

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: 'List the available Bundesbank statistics dataflows' with specific context that each dataflow is a series collection queryable via get_series. It distinguishes itself by mentioning the operation is listing, and the inclusion of well-known flow IDs adds specificity.

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 connects to get_series as the way to query data inside a dataflow, and explains that passing a flowRef fetches a single dataflow with its DataStructure reference. While it doesn't state explicit exclusions or mention the sibling dataflow_structure tool, the context is clear enough for an agent to decide when to use this tool.

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