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

Since no annotations are provided, the description carries the behavioral transparency burden. It does disclose useful behavior beyond the name, such as the editorial block being 'merged at runtime from the static articles index' and the freshness/size signal purpose. However, it does not describe any side effects, auth requirements, or response format. Overall, it gives moderate, but not complete, behavioral insight.

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 economically structured: a single dense leading sentence enumerating the content, followed by one short sentence stating the intended use case. There is no fluff, and the most distinctive features are front-loaded in the list.

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?

Given the absence of parameters and output schema, the description is nearly complete for an agent deciding how to invoke it. It specifies both what is included and why it would be used. It could be strengthened by naming the sibling tools it is not, but the provided context is enough to understand the tool's role.

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 baseline score is 4. The description does not need to add parameter information because the schema already contains no properties. The description goes a step further by clarifying the kind of detailed output the tool produces, which is more than sufficient for a no-parameter 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 opens with a specific verb and object, 'Return corpus stats', and then enumerates a detailed breakdown: total/free/premium counts, per-category counts, tag count, dates, recent updates, feed URLs, and an editorial block. This clearly distinguishes the tool from siblings like get_corpus and get_full_corpus because the focus is aggregated statistics, not corpus content.

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 provides explicit context for when to use this tool: 'A small freshness/size signal to poll before deciding whether to re-ingest.' It clearly communicates the polling use case, though it does not explicitly name alternatives or exclusions. This is solid practical guidance with only minor ambiguity about how it compares to other list/resource tools.

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