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

Annotations already cover the read-only, idempotent, closed-world safety profile, and the description goes well beyond them: publisher figures are non-comparable across companies, missing figures mean not reported rather than zero, national-security values stay banded, and aggregates cannot prove individual data requests. These are exactly the interpretive caveats an agent needs to avoid drawing false conclusions.

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?

Each sentence carries real information — the caveats about aggregation, missing values, and bands all matter for correct interpretation. The sector note is slightly redundant with the schema, and the caveats could be ordered more tightly, but there is no filler.

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 does the necessary work of explaining that the result is per-publisher headline rows with labels and how to read them. Combined with the safety annotations, an agent knows enough to call it correctly; only the sibling comparison 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?

Schema coverage is 100% and the single enum parameter is fully documented in the schema, including the no-add/no-rank note. The description's 'optionally restrict to one sector' adds nothing beyond the schema, 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 a specific verb and resource: it shows the latest headline row per publisher from the MORVS Government Data Demand Register, paired with each figure's label. That is far more specific than the title alone. It does not name or differentiate itself from its closest sibling, data_demand_source, which keeps it short of a 5.

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 states the optional sector filter and, importantly, tells the agent how to interpret the output (never add or rank across companies, missing means not reported). But it gives no explicit when-to-use guidance and never points to data_demand_source or data_broker_check as the alternative when a different view is wanted, so routing must be inferred.

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