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

With no annotations, the description carries the full burden and does well: it discloses the history start date (2026-07-26), the per-product time-series shape, the all-products default, and the explicit caveat that live shop prices are authoritative. Auth, rate limits, and pagination are unaddressed, keeping it from a 5.

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 purpose and scope, with the field legend (d, p, pl, ph, pm) packed efficiently into parentheticals. Dense but every clause earns its place given the absence of an output schema; slightly hard to parse.

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?

No output schema exists, yet the description provides the return-field legend and scope, which is exactly what an agent needs to interpret results. Complete for a read tool, with minor gaps around pagination and access constraints.

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 baseline is 3, but the description adds meaning beyond the schema by explaining the default behavior when the optional produkt_id is omitted (history of all products in the dataset). That is a genuine semantic addition over the schema text.

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?

States a specific verb+resource: it delivers the editorially-observed price history (Preis-Radar) as a per-product time series. It explicitly distinguishes itself from a live price comparison and clarifies scope, so an agent can tell it apart from siblings like produkt_details.

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 a useful when-not caveat ("Kein Live-Preisvergleich — maßgeblich ist der Preis im Shop") and describes the no-produkt_id fallback, implying usage. However it never names or routes to the sibling alternatives (produkte_suchen, produkt_details) or states prerequisites, so guidance remains implied rather than explicit.

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