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

No annotations are provided, so the description carries the full burden of behavioral disclosure. Since this is a read-only informational tool with zero parameters, the risk surface is low. The description discloses the scope of information (documents, layers, licenses, counts). However, it does not disclose the return format structure or whether counts follow any particular convention, though an output schema exists to cover this.

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 description is a single, efficient sentence that names the tool's purpose and enumerates its output categories. Zero wasted words, front-loaded with the key phrase 'What's in the corpus'. A question format is used effectively for a quick-overview tool.

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?

This is a simple parameterless informational tool with an output schema that documents return values. The description adequately conveys the purpose and scope. Given the low complexity (no params, no nested objects) and the output schema covering return structure, the description is reasonably complete. It could optionally note whether results depend on authentication/license access, but that's a minor gap for a corpus-overview tool.

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 0 parameters, so there are no parameter semantics to clarify. Per the rubric, 0 params = baseline 4. The description appropriately focuses on what the tool returns rather than inputs, which is the correct emphasis for a parameterless tool.

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 'What's in the corpus: documents, layers, licenses, and counts' clearly states the tool reports corpus contents (documents, layers, licenses, counts). It uses a specific noun phrase and enumerates the specific categories of information returned, distinguishing it from sibling tools that operate on passages, entities, or individual works.

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 implies the tool is for getting an overview of corpus contents (a 'what's in the corpus' overview tool), which is clear context for when to use it. However, it does not explicitly state when NOT to use it or name alternatives—e.g., if you need a specific document's content, use read_work. The context is implied rather than explicit.

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