Shop strukturiert analysieren

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

With no annotations provided, the description carries the transparency burden. It discloses the response structure (strict separation of 'fakten' and 'kennzahlen'), the deliberate absence of ready-made recommendations, and the rate-limit impact of include_inventory. It does not explicitly state that the tool is read-only, but the wording 'sammelt' and 'berechnet' strongly implies no side effects.

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 description is a single, dense paragraph with clear examples and a notable structural note about response formatting. It is not excessively long and every sentence provides useful context, though it could be tightened slightly by removing redundant examples.

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?

Given the tool's complexity (aggregates shop, listing, section data and computes several metrics), the description provides a good overview of purpose, metrics, output separation, and optional behavior. It lacks an explicit return format but intentionally leaves interpretation to Claude, and the absence of an output schema is compensated by the description's clarity on facts vs. metrics.

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?

Input schema covers both parameters fully with descriptions. The description adds context by mentioning 'optional niedriger Bestand je Variante', which maps to include_inventory and clarifies its analytical purpose. It does not repeat parameter details, but adds value beyond schema by highlighting the metric it enables.

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 clearly states the tool's action ('Sammelt Shop-, Listing- und Section-Daten und berechnet daraus objektive Kennzahlen') and provides concrete metric examples (Preisspanne, Aufrufe, etc.). This distinguishes it from sibling tools that fetch raw data (e.g., etsy_get_shop, etsy_list_listings) by emphasizing its analytical aggregation role.

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?

The description implies usage for holistic shop analysis and mentions optional inventory fetching, but it does not explicitly state when to use this tool instead of the individual get_* siblings, nor does it provide exclusions or alternative recommendations. The guidance is implicit through the analytical nature but not directly stated.

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