Xavio Storefront

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

Without annotations, the description carries the full burden. It discloses that the quote is firm and expires in 5 minutes, and indicates it returns a quote_id for authorization. No contradictory information.

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 sentences, concise and to the point. Every sentence adds value: first defines the action and scope, second describes the output and next step. No unnecessary words.

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 tool has one parameter and no output schema, the description is fairly complete. It covers the action, return value, and next step. It lacks explanation of parameter constraints (e.g., product_id format, qty limits), but these are in the schema.

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 coverage is 0%, but the description does not elaborate on the 'items' parameter beyond implying it is a set of items. The schema already defines the structure, but the description adds no additional meaning about fields like product_id or qty.

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 creates a firm 5-minute checkout quote and returns a quote_id. It distinguishes from sibling tools like get_product, search_shop_catalog, and search_shop_knowledge which serve different purposes.

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 when a checkout quote is needed and provides the next step (passing quote_id to authorize endpoint). It does not explicitly state when not to use or compare with alternatives, but the context is sufficiently clear.

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 full burden. It only states the verb 'Fetch' but does not disclose any behavioral traits such as error handling, authentication requirements, or whether it returns null or throws an error if the product is not found.

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, concise sentence with no unnecessary words. It is directly front-loaded with the essential information.

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 tool's simplicity (one parameter, no output schema), the description is adequate but minimal. It does not mention return format or error cases, which would be helpful for completeness.

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 the one parameter, so the schema already documents the parameter. The description adds no additional meaning beyond what the schema provides, earning a baseline score of 3.

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 'Fetch' and resource 'one product', with clear identifier 'Xavio product id'. It clearly distinguishes from siblings like create_quote and search_shop_catalog, which have different purposes.

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 when you have a specific Xavio product id, but it does not provide explicit guidance on when to use this tool versus search_shop_catalog for finding products by other criteria, nor does it state when not to use it.

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 burden. It states the tool returns in-stock products and lists returned fields, which is adequate for a read-only search. However, it lacks details on pagination, error handling, or requirements (e.g., does it require authentication?).

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?

Extremely concise: one sentence that clearly states the action and output. No unnecessary words. Front-loaded with the core function.

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 search tool with no output schema, the description adequately explains what the tool does and what it returns (price, availability, URL, merchant). It specifies 'public' and 'in-stock', adding useful context. Missing guidance on sibling tools is a minor gap.

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 coverage is 100% with descriptions for all 4 parameters. The tool description adds no additional meaning beyond the schema; it only restates that it searches and returns products. Baseline score of 3 applies.

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 searches the public Xavio catalog and returns specific fields (price, availability, URL, merchant). It distinguishes from sibling tools implicitly by focusing on catalog search, but doesn't explicitly differentiate from search_shop_knowledge or get_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?

No guidance on when to use this tool versus alternatives. It doesn't mention when not to use it or suggest other tools like get_product or search_shop_knowledge for specific cases.

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 full burden. It only mentions 'search' and 'passages' but does not disclose whether the tool is read-only, any side effects, rate limits, or return format. This is minimal transparency for a search 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?

Two sentences, no redundancy. The first sentence defines scope, the second gives concrete usage examples. Every word contributes value.

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?

Without an output schema, the description should explain what the tool returns (e.g., result format, ranking). It only mentions 'passages' via the k parameter. This leaves gaps for an agent relying solely on the 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?

Schema coverage is 100% with descriptions for all properties. The description adds slight context (e.g., 'that store's docs' for host, 'the shopper's question' for query) but does not significantly enhance understanding 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 clearly states the tool performs semantic + keyword search over Xavio's commerce knowledge, including merchant product details, policies, FAQs, and buying guides. It provides specific examples of questions it answers (sizing, materials, returns, shipping), distinguishing it from siblings like 'search_shop_catalog' or 'get_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?

The description explicitly says when to use: 'before recommending a product' to answer specific types of questions. While it doesn't name alternatives or exclusion cases, the context is clear enough for an agent to infer this is the right tool for knowledge-based queries.

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