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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the description's job is to add context — and it does: it discloses the license (CC BY 4.0, implying attribution obligations) and that the response includes a DOI to cite. It does not mention payload size or format beyond 'CSV', which is a minor gap.

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?

A single sentence that front-loads the dataset identity, then gives the key figures, then the return payload and citation requirement. No filler and no redundancy with the annotations.

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?

With no output schema and no parameters, the description still tells the agent exactly what comes back (CSV + DOI) and under what license, which is everything needed to call and correctly use the result.

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 tool takes zero parameters, which is the baseline-4 case; there is nothing to disambiguate. The description also makes clear the call is parameterless in effect by describing a fixed, single dataset.

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?

States a specific resource (Helsama's open HPLC-UV cannabinoid dataset) and a specific action (returns the CSV plus DOI), plus the concrete content it covers (CBDA in Gotland vs Italy hemp seed). Nothing among the get_article/get_facts/get_product siblings overlaps with this dataset, so an agent can route to it unambiguously.

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 dataset scope implicitly signals when to call it (questions about this specific CBDA comparison), but there is no explicit statement of when to use it versus alternatives or when not to. For a zero-parameter tool with a narrow, unique payload the implied usage is largely adequate, but no routing guidance is given.

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