verdonz_ask

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

With no annotations, the description carries the full burden of behavioural disclosure and fails to meet it. It does not say whether the call is read-only, whether it requires an existing datasetId, whether the question must reference listed metrics, or whether any state is created, so an agent cannot predict the operation's side effects.

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?

It is a single short sentence with no wasted words, so it is concise, but the brevity comes from under-specification rather than tight editing. There is no front-loaded guidance and no structural separation of purpose from usage.

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 four-parameter tool with a nested object, no annotations, no output schema, and five sibling tools, the description is not complete enough to invoke correctly. It omits the parameter contract and any result expectations, which nothing else in the definition compensates for.

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?

Four parameters including a nested timeRange object at 0% schema description coverage, and the description mentions none of them. In particular, context, datasetId, and timeRange are entirely undocumented in both places, leaving semantics like format, required pairing, and nesting keys unknown.

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 gives a verb ('Ask') and a resource ('business question') but the mechanism phrase 'through Verdonz governed semantic data' is marketing-flavoured rather than specifying the data domain. It does not distinguish this tool from siblings like verdonz_investigate or verdonz_get_evidence, which sound like equally plausible entry points for a question.

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?

There is no statement of when to use this tool versus verdonz_investigate, verdonz_list_datasets, or verdonz_get_metric, and no prerequisites or exclusions. The agent is left to guess whether 'ask' is the top-level entry point or a follow-up to another tool.

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