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

Beyond the readOnlyHint and idempotentHint annotations, the description adds valuable behavioral context: the contribution ceiling cap and the fact that the aktueller Rentenwert can differ for the two halves of the year. It also clarifies that an optional total points input projects the gross monthly pension, which is not evident from annotations alone.

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 sentence that packs the legal reference, year range, calculation logic, and optional function. It is front-loaded with the core purpose and avoids redundant filler. However, it includes several technical German terms (Entgeltpunkte, Durchschnittsentgelt, aktueller Rentenwert) that may add cognitive load, keeping it just below a 5.

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?

The tool is a straightforward calculator with 4 parameters and an output schema, so the description does not need to explain return values. It covers the key calculation aspects (ceiling cap, half-year Rentenwert) and the optional projection mode. It is complete enough for a typical agent to use correctly, though it could mention edge cases like invalid years, but the schema already constrains valid years.

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?

The input schema already covers all parameters with clear descriptions (100% coverage). The description adds formula-level context (e.g., contribution ceiling, Durchschnittsentgelt) that helps interpret grossAnnual and year, but it does not significantly expand on parameter semantics beyond what the schema provides. This aligns with the baseline score of 3.

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 identifies the tool as a calculator for German pension points (Entgeltpunkte) across 2023-2026, specifying the formula inputs (gross salary, Durchschnittsentgelt, contribution ceiling, aktueller Rentenwert). It is specific about the resource and scope, but lacks an explicit verb like 'calculate' or 'compute', which slightly lowers the score.

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 through the year range and the optional totalPoints parameter for pension projection, but it does not explicitly contrast with alternative tools or state when to use this tool versus others (e.g., de-net-salary). The legal reference and German-specific terminology strongly imply a niche use case, but no exclusions or alternative guidance is given.

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