get_beschluesse_by_departement

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

Annotations already mark the tool as read-only and idempotent, so the description adds value by specifying that results are public ('öffentliche') and listing return fields. However, it omits details like default limit (50), max limit (200), or that pagination is handled via the limit parameter – important behavioral details for an AI agent.

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-structured with a clear first sentence, usage example, and separate Args/Returns sections. It is moderately concise, with only a few redundant details (e.g., departement codes already in schema). No wasted sentences.

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 has 5 parameters (1 required), an output schema, and safe annotations, the description covers the essential behavior: what is returned (list with fields), scope (public, by department, optional date range). It is complete enough for an agent to understand the tool's function without additional context. Minor omission: no mention of empty results or error conditions.

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 provides rich descriptions for each parameter (departement with examples, date formats, limit range, format enum). The description's 'Args' section largely duplicates this information without adding new semantic meaning, so it adds marginal value beyond the schema.

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 returns all public city council decisions by department, using a specific verb (gibt zurück) and resource (Stadtratsbeschlüsse eines Departements). It provides a usage example (SSD in a quarter/year) which helps distinguish from sibling tools like detail or search, though not explicitly contrasted.

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 suggests use for institutional analyses and gives an example scope (department and time period), implying when to use it. However, it does not provide explicit guidance on when to avoid this tool or mention alternatives (e.g., search_stadtratsbeschluesse for complex filters).

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