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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds that the result is an exhaustive enumeration of all published subjects (no filtering), which is genuinely useful context. It omits any note on scale or result size, though the schema's limit notes the envelope reports the true total.

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 compact clauses: what the rows contain first, then how to use the result. Zero filler and no restatement of the title.

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?

With no output schema, the description carries the burden of describing row contents and does so concretely (subject, years forecast, vintage count). Combined with 100% schema coverage on paging, an agent has enough to call it correctly. Only the expected result volume is unaddressed.

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?

Schema description coverage is 100%, so both parameters (limit, offset) are fully documented including the default and the true-total envelope behavior. The description says nothing about paging or params, so the baseline 3 applies.

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 the resource (published forecast subjects) and the exact payload per row: each year forecast and the count of vintages. That is more specific than 'list figures' and lets an agent predict the shape of the listing. It differentiates only against figure_history, not against other listing siblings like list_sources or find_fabs.

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 use case with a named follow-up: 'Use it to find a subject_id for figure_history', which is a clear cue for the resolve-then-query workflow. It stops short of exclusions — it doesn't say when to use find_fabs or fab_profile instead when the agent already knows what it wants.

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