Generiert Wunschrufzeichen-Vorschläge basierend auf Namen und Präferenzen. Berücksichtigt Verfügbarkeit, Phonetik und CW-Freundlichkeit.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Vor- und/oder Nachname | |
| max_results | No | Maximale Anzahl Vorschläge | |
| exclude_club | No | Keine X-Präfixe (Klubrufzeichen) vorschlagen | |
| min_phonetic_score | No | Mindest-Phonetik-Score (0-1) | |
| preferred_district | No | Bevorzugtes Bundesland (1-9) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool considers availability, phonetics, and CW-friendliness, which adds meaningful behavioral context. However, it does not mention whether results are based on live data, any limitations, or the nature of the return value. Since this is a non-destructive generation tool, the lack of detail is acceptable but not fully transparent.
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 two concise sentences. The first sentence front-loads the verb and resource, and the second sentence adds relevant criteria. No filler or 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?
The tool has 5 parameters and no output schema. The description explains the core purpose and criteria, which is sufficient for a user to understand what the tool does. It could specify the return format (e.g., list of suggestions with scores), but overall it is adequately complete for a suggestion-generation tool.
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 has 100% description coverage for all 5 parameters, so the schema already provides detailed meaning for each field. The description adds general context about which factors are considered (availability, phonetics, CW-friendliness) but does not add specific parameter-level semantics beyond the schema. Baseline 3 is appropriate.
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 uses a specific verb 'Generiert' (generates) with a clear resource 'Wunschrufzeichen-Vorschläge' (desired call sign suggestions) based on name and preferences. It clearly distinguishes from sibling tools like callsign_available (availability check) and callsign_validate (validation) by focusing on suggestion generation.
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 for generating call sign suggestions and mentions criteria (availability, phonetics, CW-friendliness), but it does not explicitly state when to use this tool versus alternatives or provide exclusions. The context is clear from the purpose, but explicit guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation: calculations for different physical quantities, separate callsign functions for lookup, validation, suggestion, and availability, and band plan queries. No two tools appear to perform the same action, making selection unambiguous.
Most tools follow a verb_noun convention (calculate_, check_, list_), but the callsign_* group consistently places the noun first (callsign_lookup, callsign_validate). This split is readable but represents a mixed convention that slightly reduces predictability.
With 17 tools, the server is above the ideal 3-15 range and falls into the borderline 'feels heavy' category. While every tool has a distinct purpose, the number may be slightly unwieldy for quick selection.
The toolkit covers a broad range of amateur radio calculations (battery, cable, EIRP, wavelength, SWR, power) and callsign operations (lookup, validate, suggest, availability, database info). Some advanced features like propagation prediction are absent, but the core domain is well covered without critical gaps.
