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

No annotations are provided, so the description carries the full burden. It discloses what the tool returns (columns, numeric indicators, row count, provenance banner) and the expected usage behavior (call first). For a zero-parameter introspection tool, this is adequate transparency; no side effects are indicated, and the tool's nature makes them unlikely.

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 short sentences with no filler: the first enumerates the return contents, and the second gives the usage directive. Every word earns its place, and the key information is front-loaded.

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?

Although there is no output schema, the description explicitly lists everything the tool provides. With zero parameters and a simple introductory role, nothing an agent needs to decide whether to call this tool is missing.

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 has zero parameters, so the rubric baseline is 4. The description adds useful context about what an agent will learn from the call, and there are no parameter semantics for the description to clarify.

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 names a specific resource (the Coshhvo dataset) and lists concrete outputs: columns, numeric flags, row count, and provenance banner. The imperative 'Call this first to learn the schema' makes its role clear and distinguishable from sibling tools that focus on rows, stats, search, or comparison.

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?

It gives an explicit when-to-use instruction: 'Call this first to learn the schema.' It does not spell out when not to use it or explicitly name alternatives, but the 'first' ordering and schema-learning purpose provide clear context for an agent choosing among siblings.

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