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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it is safe. The description adds value by listing the specific metadata categories (freshness, coverage, provenance, limitations, access status), which goes beyond the generic safety profile. It does not contradict any annotation and provides contextual detail about 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 a single, compact sentence that immediately states the action and lists the key attributes. There is no fluff or redundancy, and the critical information is front-loaded. It earns its place without verbosity.

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?

The tool takes a single simple parameter, has a declared output schema (which covers return values), and annotations cover safety semantics. The description adequately specifies what metadata is described. It does not mention error handling or edge cases (e.g., missing dataset), but for a read-only retrieval tool with a well-defined output schema and annotations, this is sufficient. A 5 would require covering additional operational details that are not essential here.

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 schema has only one parameter, dataset_id, which is self-explanatory and requires no additional semantics. The description does not explicitly mention dataset_id, but the phrase 'a dataset’s' implicitly signals that a dataset identifier is needed. With 0% schema coverage, the description could have elaborated on how to format the ID, but given the simplicity of the parameter and the clear resource reference, a baseline score of 3 is appropriate.

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 uses the specific verb 'Read' followed by the resource 'a dataset’s' and enumerates the concrete attributes (freshness, coverage, provenance URLs, limitations, access status). This clearly distinguishes it from siblings: search_datasets is for finding datasets, get_dataset_sample_link retrieves a sample, and describe_dynamik likely covers a different scope. The purpose is unambiguous even without consulting the schema.

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 implies when to use the tool (when you need dataset metadata), but it does not explicitly state when to avoid it or mention alternatives. There is no reference to sibling tools or exclusions, leaving the agent to infer the context. This meets the 'implied usage' level but not the 'clear context with exclusions' bar.

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