bestand_statusTrennt die neueste verfügbare Publikation von der lückenlos verifizierten Grenze und meldet den Datenqualitätsstatus. Nutze dies, bevor du dich auf eine Auskunft verlässt — und nenne dem Nutzer die verifizierte Grenze.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish a safe read-only, idempotent, open-world operation. The description adds meaningful behavioral context beyond that: it distinguishes the newest publication from the verified boundary and instructs the agent to communicate the verified boundary to the user. No contradiction with annotations.
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?
Two compact sentences with no filler. The first sentence states the output and distinction, and the second gives a clear usage directive. The most important guidance is front-loaded.
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?
For a parameterless, read-only status tool, the description covers what it reports and when to use it, and the annotations cover safety and open-world semantics. It does not specify the exact response structure, but with no output schema the conceptual output is still described adequately.
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 zero parameters, so the description cannot add parameter-level detail; per the baseline for 0-parameter tools this is sufficient. The empty schema is fully documented and nothing is left undocumented.
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 states a clear, specific action: it separates the newest available publication from the fully verified boundary and reports data-quality status. This makes the tool's role distinct from siblings like firma_suchen or uid_pruefen: it is about the reliability and currency of data, not about retrieving entity details.
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?
It explicitly tells the agent when to invoke it: before relying on any answer ('Nutze dies, bevor du dich auf eine Auskunft verlässt'). It also instructs the agent to surface the verified boundary to the user. It does not name when-not-to-use or contrast with an alternative, so it stops short of a 5.
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.
The six tools cover clearly distinct operations: search, details lookup, risk summary, UID validation, daily briefing, and data-quality status. There is only mild overlap between firma_details and firma_risiko, since both include register findings, but their descriptions make the boundary clear.
Tool names mix German and English terms, noun compounds like bestand_status, and verb-final constructions like uid_pruefen and firma_suchen. The underscore style is consistent, but the grammatical pattern is not.
Six tools is well-scoped for a company-register information server. Each tool has a clear purpose and none feels redundant or missing within the set.
The domain is read-only Swiss company register data, and the set covers the full workflow: validate UID, search, get details, get risk-relevant publications, receive daily changes, and check data quality. There are no dead ends.