Lists loaded cross-linguistic datasets with release versions, coverage, licenses, and citation details, helping users identify and cite the correct source.
List the loaded datasets with their release versions, coverage, licenses and how to cite them.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered there. The description adds that entries carry release version, coverage, license and citation metadata, which is genuine extra context, but says nothing about result ordering, whether all datasets are returned or only 'loaded' ones are filtered out, or whether the list is complete.
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 front-loaded sentence with no filler. Every element (loaded datasets, release versions, coverage, licenses, citation) earns its place by telling the agent what comes back.
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 zero-parameter, read-only listing tool with full annotations and an output schema, the description covers scope and payload fields adequately. The only gap is the lack of any note about what "loaded" means or how complete/ordered the listing is.
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, so there is nothing for the description to disambiguate and the baseline is 4. Schema coverage is 100% and the empty argument object is self-evident.
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 and resource ("List the loaded datasets") and enumerates the metadata returned: release versions, coverage, licenses, citation info. That makes the tool's purpose clear without opening the schema. It doesn't contrast itself against siblings, but the siblings (find_language, get_feature, crosstab, etc.) are different enough that confusion is unlikely.
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?
Usage is only implied: an agent infers this is entry-point/discovery tooling because it returns dataset-level metadata. There is no explicit when-to-use statement and no mention of alternatives for a caller who actually wants feature or value data (e.g., search_features, get_values).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.