epl_gesuchseingaenge

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

Annotations already declare readOnlyHint=true, which the description complements with 'abrufen' (retrieve) and 'Transparenzliste'. No destructive behavior is implied, and the description adds context about the official BAG list. With annotations covering safety, the description adds moderate value.

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 extremely concise: two short sentences plus a structured use_case block. The main purpose is front-loaded, and every sentence adds value without redundancy.

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 zero parameters and presence of an output schema, the description fully covers the tool's purpose and use case. It explains what information is returned (medications applied for SL) and references the official source. No gaps remain.

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 tool has no parameters, and schema coverage is 100%. Per guidelines, baseline is 4. The description does not need to explain parameters but adds value by describing what data is retrieved (current applications for SL).

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 retrieves current applications for the specialty list (SL) and specifies the action 'abrufen' and resource 'Gesuchseingaenge'. The use case further clarifies it answers which medications are being considered for SL inclusion, making it highly specific and distinct from siblings.

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 use case block explicitly states the question the tool answers ('Welche Medikamente sind aktuell zur Aufnahme in die SL beantragt?') and characterizes it as transparency/monitoring. However, it does not provide explicit when-not-to-use guidance or compare with sibling tools like epl_sl_suche.

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