Dataville

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

No annotations are provided, so the description carries the full disclosure burden. It usefully scopes the result set to sources usable by search_dataville, but for a read tool it omits any note on return shape, ordering, or cost of an empty/failed call.

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 clause (verb, resource, linkage to search_dataville) earns its place.

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?

There is no output schema, so the description would ideally say what a listed source contains (identifier, display name) so the agent can feed it into search_dataville. It names the relationship but leaves the return shape undocumented.

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 no parameter semantics to explain and the baseline of 4 applies. The schema is an empty object, consistent with the description's no-argument framing.

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 verb and resource ("List the data sources") and ties the resource to the sibling tool search_dataville, so an agent can tell it apart from a search operation. It stops short of an explicit statement of the list/search relationship, but the scope is unambiguous.

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 reference to search_dataville implies this tool is used to discover valid sources before querying, but no explicit when-to-use, prerequisites, or exclusion is given. Usage is inferable rather than stated.

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

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

No annotations are provided, so the description carries the full behavioral burden, and it says nothing about result format, result count, pagination, latency, or error behavior for an unknown source name. The only behavioral hint is that source must be a valid name from list_dataville_sources, which is thin for a search tool.

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?

Two sentences, zero waste: the first defines the operation and its inputs, the second defines when to reach for it. Front-loaded and appropriately sized.

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 annotations, the description should ideally say a little about what a query returns or how source failures surface. For a two-parameter search it is adequate for tool selection but leaves return-shape gaps.

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 coverage is 100% with both parameters documented, so the schema already carries the parameter semantics and the baseline is 3. The phrase 'keyword string' adds no syntax, format, or matching-behavior detail beyond the schema.

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 concrete verb and resource ('Query one of Dataville's data sources ... with a keyword string') and explicitly points at the sibling tool that supplies valid source names. An agent can distinguish this from list_dataville_sources without opening either 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?

Gives a clear when-to-use rule: prefer this over memory for verifiable facts like filings, papers, package metadata, nutrition, and census figures. It lacks explicit when-not / failure conditions, but the positive routing guidance is strong for a tool with only one sibling.

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