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

Beyond the readOnlyHint, the description discloses genuinely non-obvious behavior: `entitled: true` does not mean a product is sellable or served, `live_row_count` is a fast estimate rather than the filtered slice, and it explains the billing model (bulk annual plan, no per-call charges, search never billed). These are real traps an agent would otherwise fall into, which is exactly the value annotations cannot provide.

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 core list purpose and the product_id detail mode are front-loaded, and the caveats are marked with IMPORTANT. It is a dense wall of text in one paragraph, and the pricing/billing sentences are somewhat tangential to invocation, but overall most sentences earn their 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?

With no output schema, the description carries the burden of describing returns and does so reasonably: launch state, coverage state, entitled flag, live_row_count, row_count_basis/row_count_note, corpus_state. It names the key fields and their caveats, though it does not exhaustively enumerate the full row shape, leaving a small gap for a list tool.

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% and only one optional param exists, so the baseline is 3. The description adds meaning beyond the schema by enumerating what the single-product mode returns (unit_definition, provenance, sectoral_ds, licence, cadence, limitations), which tells the agent why to pass product_id at all.

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: listing all 14 Pauhu sectoral products with their launch/coverage/access state, plus an optional single-product detail mode. It is clearly a catalogue/state tool, distinct from the search/translate siblings, though it never names a sibling to route against. Purpose is unambiguous even without that differentiation.

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 usage context ('Customer's AI client calls this once at session start to learn product and access state') and a clear conditional for the parameter ('Pass product_id for one product's full served row'). It stops short of naming alternatives (e.g. pauhu_search or library_catalogue) or stating when not to call it, so it lands at a solid 4 rather than 5.

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