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

No annotations exist, so the description carries the full burden. It usefully discloses the sentinel semantics ('empty = still on sale'), which an agent could not infer otherwise, but says nothing about it being a read-only query, result ordering, or any limits.

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?

A single sentence that front-loads the returned data and tucks the filtering detail into a trailing clause. Slightly convoluted parenthetical, but no wasted sentences.

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 must explain the return. It conveys the two key fields and the empty-value convention, but leaves the result shape (one row per offer per supplier? per date?) and ordering unspecified.

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 0% – the lone 'supplier' parameter has no description – so the description must compensate. It does: it identifies the parameter as a supplier code, gives a concrete example ('eneco'), and notes it is an optional filter.

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 resource – offer lifecycle, i.e. first-seen-on-sale and withdrawal dates – which is clearly distinct from siblings like cheapest_history or market_summary. The verb is implicit (it returns/queries rather than acting), but the content of the result is unmistakable.

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 default scope ('across every supplier we track') and that filtering is optional, which is mild usage context. There is no guidance on when to pick this over cheapest_history or market_summary, and no exclusions or prerequisites.

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