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

Beyond the readOnlyHint annotation, the description discloses critical behavioral nuances: the 'stand' field is a server-side current date, and 'last_verified_at' is an internal maintenance date that must never be presented as 'zuletzt geprüft am' because it would misleadingly imply staleness. It also forbids exposing raw fields and mandates calling quote afterward, adding substantial context not present in 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?

The description is a single dense paragraph with no fluff; every sentence adds a rule or context. It is somewhat long, but the complexity of the tool's output restrictions and field semantics justifies the length. Front-loaded with purpose, then usage constraints, though a bulleted structure would improve readability.

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 purpose, geographic scope, field semantics, output presentation rules, and the required follow-up call to quote. An output schema exists, so return-value details are not needed. Nothing essential is missing for an agent to invoke the tool correctly and process its results properly.

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?

Schema description coverage is 100%, with energy_type already documented as 'Optional: nach Energieart filtern.' The description does not add new parameter-level semantics; it only references energy_type incidentally in an example. Baseeline 3 is appropriate because the schema carries the load.

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 opens with a specific verb and resource: 'Listet die öffentlich verfügbaren Energiefuchs/FlexEnergy-Tarife (FlexPower Neo, FlexGas Neo)'. It also clarifies the geographic scope ('bundesweit (Österreich) einheitlich verfügbar, keine PLZ-Filterung nötig'), which distinguishes it from location-dependent tools. This clearly differentiates it from sibling search_flexenergy_ratgeber, which searches articles rather than tariffs.

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 gives clear context: the tool is meant 'NUR für die interne Auswahl/Weiterverarbeitung', and afterwards one should 'IMMER quote ... aufrufen'. This effectively tells the agent when and how to use the results. However, it does not explicitly name alternatives or state when not to use this tool vs. other siblings, so it misses explicit exclusions.

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