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

Annotations already cover the read-only and open-world profile, yet the description adds genuinely useful behavior: data lag (~2 months behind), sort order (largest first), licensing ('Open Government Licence, no key'), and the x402 payment model with 'failed calls are not charged'. That billing detail is material to invocation decisions, though there is no explicit rate-limit or row-count ceiling.

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?

Front-loaded with the resource and source dataset, then grouping, then licensing and price — a sensible priority order with no filler sentences. It is dense and slightly run-on in places, but every clause carries information an agent needs.

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 read-only filtered data query with a full schema and an output schema, the description supplies everything else that matters: provenance, freshness, units, sort order, access terms, and cost. Nothing required to call it correctly 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%, so 3 is the baseline, but the description reinforces semantics the schema only sketches — 'grouped by region, ICB, GP practice or product presentation' maps the groupBy options to their meaning, and 'largest first' clarifies results ordering. It stops short of explaining default-month behavior or the interaction between area and groupBy.

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+resource (NHS England primary-care prescribing data for a drug), the source dataset (NHSBSA EPD), and the exact measures returned (items, actual cost in GBP, quantity) plus grouping dimensions. It is unmistakable against the sibling search tools, which are all news/web/academic search endpoints.

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 explains the matching rule ('match on BNF chemical substance or presentation name') and defaults, which implies when the tool fits, but it never states when not to use it or names an alternative for related needs. No sibling is a close substitute, so the gap is mild rather than harmful.

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