metabolomics_study

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does state the output fields and the query mechanism, which is reasonable transparency for a simple retrieval tool; however, it does not mention behavior for invalid IDs, missing studies, or any potential rate limits. This is a moderate disclosure, not a severe 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?

The essential information is front-loaded: the source, the resource type, the identifier format, and the returned fields appear early. The bilingual repetition adds some redundancy, but it remains compact and does not obscure the key facts, so it is still reasonably concise.

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 retrieval tool with one parameter and an output schema, the description covers the query mechanism, the source database, and the main returned content. It does not discuss edge cases like invalid accessions, but the presence of an output schema and the simple nature of the tool make this a minor omission.

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 input schema only provides a raw 'study_id' string with no description, so the description's explanation that it should be an MTBLS accession number (e.g., MTBLS1) is essential and highly valuable. It fully compensates for the 0% schema description coverage by defining the parameter format and giving a concrete example.

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 identifies the tool as retrieving EBI Metabolights metabolomics study details by MTBLS accession number, and explicitly lists the returned fields (title, description, technology, design, factors). This makes its purpose distinct from sibling tools like metabolomics_latest, which are not about retrieving a specific study by ID.

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 states that the tool is used by supplying an MTBLS number such as MTBLS1, which is clear usage guidance for the intended scenario. It does not explicitly name alternative tools or state when not to use it, but the accession-based lookup instruction provides adequate context.

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