ecoExperten Energieausweis

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

Annotations already declare readOnlyHint=true, so the description's 'abfragen' is consistent. Beyond annotations, the description adds the parameter format constraint (EA-XXXXXXXX), but does not disclose other behavioral traits like error handling or response structure. The existence of an output schema may cover return values, but description alone lacks depth.

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 sentence that front-loads the purpose and appends the format in parentheses. No wasted words; efficient and scannable.

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 simple read-only tool with one parameter and an existing output schema, the description adequately covers purpose and parameter format. It does not explain possible statuses or return values, but the output schema presumably handles that. A brief note on output type would improve it, but current completeness is sufficient.

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 0%, so the description must compensate. It provides the required parameter format (EA-XXXXXXXX) and the context of 'Bestellnummer', adding meaning beyond the schema's title. This is helpful for correct invocation, though it could detail the format more explicitly.

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 it queries the processing status of an energy certificate order (Bearbeitungsstand einer Energieausweis-Bestellung abfragen) and specifies the order number format. However, it does not explicitly differentiate from sibling tools like bestellung_pruefen, though the verb 'abfragen' and noun 'Bearbeitungsstand' indicate a status query.

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 checking order status and provides the required number format, but does not give explicit guidance on when to use this tool versus alternatives like bestellung_aufgeben or bestellung_pruefen. No when-not or alternative suggestions.

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

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

The description adds behavioral context beyond annotations: it's a binding, paid order that requires user consent. It mentions test mode allows simulation without sending. Annotations indicate non-read-only, non-idempotent, and non-destructive, which align with the description. No contradictions.

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 reasonably concise and front-loaded with the core action and price. Each sentence adds value, though it could be slightly shorter. The structure flows well from purpose to preconditions to test mode.

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 high complexity (37 params, 22 required, no schema descriptions) and presence of an output schema, the description is incomplete. It fails to explain most parameters, and does not mention what the tool returns (e.g., order ID). The agent lacks critical information to correctly invoke the 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?

With 0% schema description coverage and 37 parameters, the description must compensate but barely does. It only explains agb_akzeptiert and zahlungspflichtig_bestaetigt. All other parameters (vorname, nachname, email, etc.) receive no explanation, leaving the agent to guess their meaning and valid values.

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 is for ordering a Verbrauchsausweis (energy performance certificate) at a fixed price of 59 EUR, payable by invoice. It distinguishes from siblings by referencing bestellung_pruefen as a prerequisite, indicating this is the final order step.

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?

Explicitly states when to call: only after bestellung_pruefen returns 'bestellbar' and the user explicitly accepted the AGB and payment obligation. Also describes the test_modus parameter for simulation without sending. Provides clear conditions and alternatives.

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

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

The description states 'OHNE zu bestellen,' which aligns with the readOnlyHint: true annotation. It adds context by mentioning it checks GEG rules. Since annotations already declare read-only behavior, the description reinforces it without contradiction. No side effects are described, but that is consistent with a read-only validation tool.

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 very concise: two sentences, front-loaded with the main purpose. It efficiently lists key parameter groups in a bullet-like format without extra words. Every sentence adds value, with no 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 the complexity of 29 parameters (17 required) and 0% schema coverage, the description is too sparse. It provides a high-level overview but lacks details on many inputs, validation rules, or expected output (though output schema exists). The agent may need to guess parameter formats or allowed values for fields like 'energy_source' or 'has_vacancy'. The description is not complete enough for reliable use.

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 0%, so the description must explain parameters. It lists a few key parameters (gebaeudetyp, Adresse, Baujahre, etc.) and provides format hints (e.g., 'JJJJ-MM' for consumption_start, 'kWh Brennwert' for energy_unit). However, it does not explain many other parameters (e.g., energy_source, has_vacancy, anlass_ausstellung). With 29 parameters total, the coverage is insufficient for an agent to know expected values.

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's purpose: 'Verbrauchsausweis-Bestellung vorprüfen (Pflichtfelder + GEG-Regeln), OHNE zu bestellen.' It uses a specific verb 'vorprüfen' (pre-check) and specifies the resource ('Verbrauchsausweis-Bestellung'). It also distinguishes from siblings by noting it does not place an order, contrasting with 'bestellung_aufgeben'.

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 provides a clear usage guideline: 'Immer zuerst aufrufen.' (Always call first.) This tells the agent to use this tool before any order placement. It does not explicitly list when not to use it, but the context of siblings (bestellung_aufgeben, bestell_status) implies the workflow. The guidance is explicit enough for a prerequisite check.

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

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

Annotations already indicate readOnlyHint=true, so the agent knows it's a read operation. The description adds value by specifying the type of information returned (prices, documents, legal requirements), which aids in setting expectations beyond the annotation.

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, front-loaded sentence that immediately identifies it as 'Produktinfo' and lists the key content areas. No unnecessary words; every phrase earns its place.

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 tool with an output schema (provided but not detailed), the description adequately covers what information the tool provides (prices, documents, legal prerequisites). It is sufficient for an info-only 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 zero parameters with 100% coverage, so the description naturally cannot add parameter-specific meaning. Baseline 4 is appropriate as no further clarification is needed.

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 'Produktinfo: Energieausweis für Wohngebäude bestellen (Preise, benötigte Unterlagen, gesetzliche Voraussetzungen)' clearly states the tool provides product information about ordering an energy certificate, including prices, required documents, and legal prerequisites. It distinguishes itself from sibling tools like 'bestellung_aufgeben' (place order) and 'bestell_status' (order status) by focusing on informational content.

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 the tool should be used when users need pricing, document, or legal requirement information before proceeding with an order. It does not explicitly state when not to use it, but the sibling tool names make the distinction clear: use this for info, others for actions.

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