zh_edu_mittelschulen

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

Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds useful behavioral details: default jahr is the current year if empty, response_format can be markdown or json, and the output includes specific breakdowns. This goes beyond the annotation minimum without contradicting it.

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 well-organized: a concise summary of purpose and data scope, followed by a structured Args list and a Returns note. Every sentence adds value, and it is front-loaded with the most important information. No redundant or filler content.

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 description covers the tool's purpose, parameters, output type, and included data dimensions. This is sufficient for an agent to select and invoke the tool correctly. Minor omission is the lack of explicit mention of return format structure, but the presence of output schema and clear Returns description mitigates 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?

The Args section restates the parameter descriptions already present in the schema (mittelschultyp, jahr, response_format) but adds no new meaning. The schema provides clear descriptions, so the baseline of 3 applies; the description does not compensate beyond this.

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 purpose: showing statistics for Mittelschulen (Gymnasium, FMS, HMS) in Kanton Zürich. It specifies the exact data dimensions (Lernendenzahlen nach Mittelschultyp, Bildungsart, Geschlecht, Staatsangehörigkeit), which distinguishes it from sibling tools covering other school types or metrics.

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 use for Mittelschul statistics with clear scope (Kanton Zürich) but does not explicitly mention when to use this tool over alternatives or provide exclusion criteria. Sibling tool names give context, but the description itself lacks explicit guidance on selection.

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