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

Goes beyond the annotations by disclosing the write side effect that found logos are persisted as design assets in the account, and by clarifying that no brand is actually adopted until a separate brand_kit_save call with brandingOwnershipConfirmed. This explains the non-read-only annotation and sets expectations that the result is a reviewable proposal rather than a committed change. It does not quantify cost, rate limits, or what happens to existing brand data.

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 content is front-loaded and the proposal-then-save sequence is stated early. However, the entire description is duplicated verbatim in German and English, roughly doubling the length without adding information, which conflicts with the requirement that every sentence earn its 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?

There is no output schema, so the description must carry the return-value burden, and it does: it enumerates exactly what the proposal contains (colours, typeface mapping, logo candidates, imprint data) and where the logos are stored. A three-parameter tool with full schema coverage is adequately covered by this.

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%, so the schema already documents websiteUrl, reasoning, and maxLogoCandidates with constraints. The description adds no per-parameter semantics (e.g. how the logo count affects cost or quality), so the baseline of 3 is appropriate.

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 and resource ('Liest eine öffentliche Firmenwebsite aus und schlägt daraus ein Briefkopf-Design vor') and enumerates the concrete outputs (brand colours, mapped typeface, logo candidates, imprint data). It is clearly distinguishable from siblings like brand_kit_get and brand_kit_save, which it explicitly names as the adoption step.

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?

Explicitly frames the workflow: this tool only produces a proposal ('Das Ergebnis ist ein Vorschlag zur Abstimmung mit der Kundin oder dem Kunden'), and adoption requires a follow-up brand_kit_save carrying brandingOwnershipConfirmed. It routes the agent well, but does not state when not to use it (e.g. when a brand kit already exists and brand_kit_get should be used instead).

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