shop

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals critical behaviors: a 15-minute price binding, the response containing quote_id and net unit prices, gross price calculation (Netto x 1.19), and shipping referenced to separate terms. This goes beyond a simple action statement, though it does not mention authentication requirements or side effects like quote creation.

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 with no wasted words. The first sentence states purpose and constraint (price binding), the second details the parameter format, response contents, and price calculation. Information is front-loaded and every sentence 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?

Given the lack of annotations and output schema, the description covers the essential usage: how to pass line items, what comes back, and how pricing works. It ties into the ordering workflow. It omits the role of client_id/client_secret, but those have defaults and are likely authentication metadata; the description is otherwise complete enough for an agent to select and call the tool correctly.

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 no descriptions and 0% coverage. The description compensates for the required 'positionen' parameter by specifying its exact structure ('Liste aus {"sku": "...", "menge": n}'), which is essential. However, it provides no additional meaning for 'client_id' and 'client_secret', leaving those parameters undocumented. Since coverage of parameters is partial, a score of 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 clearly states the tool's action: 'Verbindliches Angebot (Quote) einholen' (obtain a binding quote), with a specific verb and resource. It distinguishes itself from sibling tools by explicitly mentioning the 15-minute price lock and the resulting quote_id used for bestellung_aufgeben, making its purpose unambiguous.

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 when to use this tool: before placing an order, as it provides the quote_id for bestellung_aufgeben. It references the ordering workflow but does not explicitly state when not to use it or list alternatives. This is clear context without formal exclusions, matching a 4.

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?

No annotations are provided, so the description carries the burden of behavioral disclosure. It meaningfully describes a valid-quote requirement, prepayment terms, identical billing/shipping addresses limited to DE/AT, server-side checks on order amount and daily limits, and email confirmation. It does not cover all failure modes, but it goes well beyond a minimal mutation statement.

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 compact and front-loaded with the core purpose. Each sentence adds a distinct constraint or behavior: quote validity, prepayment, address rules, server-side limits, and email confirmation. There is no filler or unnecessary repetition.

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 core workflow is clear enough to place an order with the required parameters. However, with 10 parameters, no annotations, and no output schema, the description does not document the optional referenz/auth parameters, response/return behavior, or error cases. It is adequate but has clear gaps.

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 adds meaning to quote_id ('gueltige Quote'), to address fields (identical DE/AT addresses), and to email (confirmation destination). However, it leaves referenz, client_id, client_secret, and land semantics unexplained, so compensation is incomplete.

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 a specific verb-plus-resource purpose: 'Bestellung zu einer gueltigen Quote aufgeben' (place an order for a valid quote). It also distinguishes this from sibling tools like angebot_einholen and bestellung_status by focusing on order placement rather than quote creation or status lookup.

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 usage context is implied rather than explicit: it is for placing an order against an already valid quote, with prepayment and identical DE/AT addresses. The description does not explicitly name alternatives or state when not to use this tool, so the guidance is adequate but not fully explicit.

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?

With no annotations, the description carries full responsibility for behavioral disclosure. It reveals that the order must be one's own ('eigene Bestellung') and that tracking numbers appear only after shipping, but it omits authentication requirements, error behavior, and any effects of client_id/client_secret.

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, compact sentence with no wasted words. It front-loads the core function and adds one relevant detail (tracking number), though it largely mirrors the tool name.

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 tool with three parameters, no annotations, and no output schema, this description is insufficiently complete. It does not explain the required order_id format, the role of client_id/client_secret, or any auth prerequisite, so an agent cannot reliably construct a valid call.

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%, yet the description makes no mention of any parameters. An agent is left with only the schema's field names (order_id, client_id, client_secret), which may be self-explanatory but lack the context the description should provide.

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 the tool's function: it retrieves the status of one's own order, including tracking number after shipping. This distinguishes it from siblings like bestellung_aufgeben (place order) and angebot_einholen (get quote), though it lacks an explicit verb.

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 no guidance on when to use this tool versus alternatives. There is no mention of exclusions or conditions, leaving the agent to infer usage from the tool's name.

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?

With no annotations, the description carries the full burden of behavioral transparency. It provides no information about side effects, read-only nature, return values, or prerequisites. The description is purely declarative and reveals nothing about what happens when invoked.

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 concise in length but not in substance. It uses a single non-actionable sentence that fails to convey the tool's purpose, making it under-specified rather than efficiently informative.

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?

Although the tool has no parameters and no output schema, the description still fails to explain what the tool returns or what conditions are indicated. An agent cannot infer how to use this tool correctly based solely on this description.

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 and the input schema is empty, so the description is not required to explain parameter meaning. The baseline for 0-parameter tools is 4, and the description does not actively mislead; it simply adds no value beyond the schema.

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 is a noun phrase ('Rahmenbedingungen fuer maschinelles Einkaufen in diesem Shop') without a specific action verb or resource. It states a topic but not what the tool actually does, and it does not differentiate itself from sibling tools that likely retrieve terms or conditions.

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?

There is no guidance on when to use this tool versus the siblings (angebot_einholen, bestellung_aufgeben, etc.). No exclusions, no context, no alternatives are mentioned.

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?

With no annotations to cover behavior, the description takes on the full burden and discloses an important trait: the price is just the current catalog price and is not a binding offer until angebot_einholen is used. This is a valuable behavioral warning that goes beyond the simple 'get details' purpose. It also lists the kind of data returned. It does not mention error cases or side effects, but for a likely read-only tool, the pricing caveat is the most critical behavior.

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 concise, with two short sentences. The first sentence states the core purpose and content, while the second adds a crucial caveat about pricing and the follow-up tool. There is no fluff, and the most critical differentiator (binding price) is clearly separated.

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 adequately covers the intended use case: retrieving detailed product information for an article. It lists the types of data included (description, technical specs, datasheet) and warns about the non-binding nature of the price, which is an essential detail in a sales context. With no output schema, this description gives the agent enough insight into what to expect, though it does not specify how to handle missing or invalid SKUs.

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 schema has no description for the 'sku' parameter (0% coverage), so the tool description must compensate. It says 'Details eines Artikels' which implies the SKU identifies an article, but it does not explicitly state that the sku parameter is the article identifier or provide format/reference guidance. The parameter name itself is self-explanatory, so a moderate score of 3 is appropriate; there is some semantic linkage but not thorough.

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 identifies the resource (Artikel) and the content type (Beschreibung, technische Daten, Datenblatt), implying that the tool retrieves detailed information for a single, known product. It does not explicitly use an action verb like 'liefert' or 'ruft ab', and it does not explicitly contrast it with sibling tools, but the focus on a single article's details distinguishes it from tools like produkte_suchen.

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 context that the returned price is a non-binding catalog price and states that it becomes binding only through angebot_einholen with a 15-minute price binding. This effectively tells the agent when a price from this tool is insufficient and directs them to the correct complementary tool. However, it does not generalize to when to use this tool versus other sibling tools beyond the pricing scenario.

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 discloses that the tool returns deliverable (lieferbare) articles with gross prices (incl. VAT) and availability class, and states that prices are non-binding until a quote. This adds context about result filtering and pricing caveats, which is useful beyond the schema. However, it doesn't mention any constraints such as authentication, rate limits, or handling of out-of-stock items beyond the availability class. Given no annotations to lean on, the description carries the burden but still omits a few behavioral details.

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 dense sentences: the purpose is front-loaded in the first sentence, and the second adds behavioral context and a pointer to the quote tool. Every sentence contributes value without verbosity.

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 is low-complexity with two parameters and an output schema present, reducing the need to explain return values. The description covers search term types, result contents, and the pricing caveat, which suffices for basic use. Minor gaps remain (e.g., result ordering, max results detail), but these are lower-risk.

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 explains the 'suchbegriff' parameter by specifying it accepts title, article number, or EAN, which goes beyond the bare schema. But 'max_treffer' is not described in the text; the schema only shows a default value and 'Max Treff' title. This incomplete coverage of one parameter with zero schema descriptions makes the help insufficient.

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 specific verb ('suchen'), a clear resource ('Produkte im Katalog'), and the search dimensions (Titel, Artikelnummer, EAN). It unambiguously identifies what the tool does and implicitly distinguishes it from tools like produkt_details, which retrieves a specific product.

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 indicates its primary use as a catalog search and, importantly, names the sibling 'angebot_einholen' as the tool for obtaining binding quotes, noting prices are non-binding until quoted. This gives the agent a clear when-to-use vs. when-not-to-use signal, though it doesn't mention explicit exclusions or alternatives in detail.

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