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

No annotations exist, so the description carries the full disclosure burden. It does reveal the meaningful behavior — returning only published years, the count of covering reports, and the themed annual edition. However, it does not mention ordering, handling of unrecognized years, or response format, so transparency is adequate but not rich.

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 filler. The return payload is front-loaded in the first sentence and the usage trigger in the second; every word 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?

For a zero-parameter, low-complexity list tool with no output schema, the description covers what is returned, the scope (published years), and when to invoke it. Minor gaps like sort order or empty-result behavior are small enough not to seriously impair a correct call.

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 (empty schema, 100% coverage vacuously), so there is nothing for the description to elaborate on. Baseline 4 applies for 0-param tools, and the description appropriately spends no words on parameters.

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 states a specific verb and resource ('Return every published year') and adds detail on the exact payload shape (report count, themed yearbook/edition). This clearly differentiates it from siblings like search_reports and list_catalog, which operate on report-level data rather than year-level aggregation.

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 final sentence, 'Use when the question names a year,' gives an explicit trigger condition that an agent can act on. It lacks explicit when-not-to-use phrasing or named alternatives, but the positive condition is clear and directly actionable.

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