get_dataset

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

With no annotations provided, the description carries the full burden. 'Fetch' clearly implies a read-only operation and 'full metadata' signals what is returned, but there is no disclosure of behavior on missing/invalid accessions or any edge-case semantics. This is acceptable for a simple fetch tool but not richly transparent.

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 efficient sentence that front-loads the action and object, then gives a compact illustrative example. Every part earns its place and there is no 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?

For a low-complexity tool with only two required parameters and an output schema, the description provides enough information to invoke the tool correctly. It does not describe not-found behavior, but that is not essential given the output schema and the straightforward fetch semantics.

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 description coverage is 100%, so the baseline is 3. The description repeats the schema's own examples ('geo' and 'GSE123456') without adding new parameter constraints, format details, or relationship guidance beyond what the schema already provides.

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 states a specific verb ('Fetch'), a clear resource ('full metadata for one dataset'), and the identifying parameters (source and accession). This distinguishes it from the sibling tools search_datasets and list_sources, since it targets exactly one known dataset rather than searching or enumerating.

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 example implies the tool should be used when the caller already knows the source and accession and wants full metadata for a single dataset. However, it does not explicitly mention when not to use it or contrast it with search_datasets or list_sources.

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