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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safety profile is covered. The description adds the result shape (annual kWh yield and € savings), which is genuinely valuable given there is no output schema, but says nothing about calculation assumptions or rounding.

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?

Three short sentences, front-loaded with the primary action, followed by a qualifier and the return values. Every sentence carries information; no filler.

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?

All parameters are optional with defaults and fully documented in the schema, and the missing output schema is compensated by naming the two result values. The only gap is the stray mention of 'Neigung', a factor the caller cannot actually supply.

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 all four parameters are already documented with ranges and defaults. The description only loosely maps to them ('Standort' ≈ region) and introduces 'Neigung' (tilt), which has no corresponding parameter — mildly misleading but not harmful.

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: 'Berechnen Sie den jährlichen Stromertrag Ihres Balkonkraftwerks', refined by 'Einfacher Ertragsrechner für Solarmodule'. An agent can tell this is a photovoltaic yield estimator, though siblings (bot_XXX identifiers) give no basis for explicit 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?

The description establishes clear usage context — estimate annual yield and savings for a balcony solar installation, factoring in location and tilt. It offers no explicit exclusions or named alternatives, but the scope is unambiguous enough to route correctly.

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