Levels Custom Apparel

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

Annotations already establish this as a read-only, non-destructive, closed-world operation. The description adds that facts are presented 'as the site states them,' signalling site-authored rather than computed data, but it does not discuss freshness, caching, or return format.

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 efficient sentence that packs in the relevant content categories. It is slightly list-heavy and lacks a leading verb, but every item earns its place by clarifying scope.

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 zero-parameter read-only tool with annotations and no output schema, the description covers the content domains well enough for correct selection and invocation. Additional detail about return shape is unnecessary without an output 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?

The tool takes zero parameters, so there are no parameter semantics to explain. The empty schema is fully consistent with the description, and the baseline for zero-parameter tools 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 enumerates the specific business facts returned (timings, delivery, minimums, set-up, decoration methods, samples, returns, contact details), making the resource clear. It does not include an explicit verb, relying on the title for that, but the content scope distinguishes it from product, quote, and order siblings.

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?

Usage is implied by the listed content: an agent can infer this tool is for business-policy or logistics questions rather than product details or quotes. However, there is no explicit when-to-use guidance, no exclusions, and no named alternatives such as get_product or get_quote.

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 declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the field inventory but says nothing about error behavior for a missing slug or response shape; with annotations carrying the main burden, a 3 is fair.

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?

One front-loaded sentence that states the resource first and then its contents; no filler. The colon-list style is dense but every item earns its place as a returned field.

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 single-parameter read-only tool with no output schema, the field enumeration effectively describes what comes back and annotations cover safety. Only a note on behavior for an unknown slug is missing.

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% and the single slug parameter is documented as coming from search_products. The description adds no further meaning beyond the schema, so the baseline 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 names a specific resource — one garment — and enumerates its facts (brand, fabric, fit, sizes, colours, price, link), so an agent knows exactly what it returns. It does not explicitly contrast itself with search_products or get_quote, but 'one garment' versus a search is inferable.

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?

Usage is only implied: this is the detail lookup for a single product, and the schema note says the slug comes from search_products. There is no explicit when-to-use/when-not or naming of alternatives such as search_products or get_quote.

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 declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds meaningful behavioral context beyond that: the price comes from the site's own engine, it assumes a single left-chest logo at a typical size, and exact pricing of real artwork happens on the product page. It doesn't say whether the returned price includes tiers, setup fees, or shipping.

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 tight sentences with the core promise front-loaded and the caveat second. Nothing is redundant, though the second sentence could more explicitly say 'this is an estimate' rather than leaving that to inference.

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 three-parameter, read-only pricing tool with no output schema, the description covers what is being priced and its fixed assumptions, which is the critical part. Gaps remain: no mention of the method parameter's price impact, no indication of what the response contains (unit price vs total), and no guidance on chaining from search_products.

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 67%, with slug and method documented and quantity undocumented. The description reinforces quantity ('at a quantity') but adds no tier, minimum, or volume-break semantics, and never mentions the PRINT/EMBROIDERY method choice despite it changing the price. Baseline 3 is appropriate since the schema already carries most parameter meaning.

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+resource: it returns 'a real price from the site's own pricing engine' for one garment at a quantity. It also pins the exact configuration being priced (one logo, left chest, typical size), which is more precise than the title. It doesn't name siblings like get_product or start_order, so an agent must infer the boundary between quoting and ordering.

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 product page prices the customer's real artwork exactly' implies this is an indicative figure rather than a binding price, which is useful usage context. However, it never explicitly says when to call this versus get_product or start_order, nor does it state prerequisites such as obtaining the slug from search_products (that only appears in the schema).

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 declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so safety is covered. The description adds valuable behavioral context by explaining the return shape: match counts, distribution, and the best 15 results with prices before logo and links, which tells the agent about result limits and output format.

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 tight sentences with no wasted words. The search scope and key filter dimensions are front-loaded, followed by the return behavior, making it easy to scan.

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 15 optional parameters and no output schema, the description does well by explaining the return format (match count, spread, best 15 with prices and links). It is nearly complete, though it could mention pagination or whether the top 15 is fixed.

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%, so the schema already documents all 15 parameters in detail. The description only broadly names the filter categories (category, brand, trade, colour, fabric, budget) without adding syntax or examples beyond what the schema provides, making the baseline score of 3 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 uses a specific verb ('Search') and resource ('every garment Levels sells') and lists the filter dimensions, making the tool's purpose immediately clear. It does not explicitly contrast itself with sibling tools like get_product, but the search-oriented scope is distinct enough for an agent to distinguish it.

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 filtered browsing by listing dimensions, but it gives no explicit guidance on when to choose this tool over get_product, get_quote, or start_order. No prerequisites or exclusions are stated, leaving the agent to infer the right context.

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 declare readOnlyHint=true and destructiveHint=false, so the description's main job is domain-level context. It delivers that by explaining the tool produces no state change until the customer completes the flow externally ('nothing is ordered until they finish it'), which is meaningful beyond the annotation. It does not describe the exact return shape (one link vs. two fields), leaving a small gap.

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, and the key behavioral caveat (nothing is ordered yet) is stated up front. The phrasing of the opening clause is slightly convoluted but still short.

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 one-parameter, read-only tool with no output schema, the description covers what an agent needs: it returns links for the customer, one for ordering and one for a sample, and no order is placed by the call. Only a clearer statement of the exact return contents is missing.

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?

There is a single parameter with 100% schema description coverage, and the schema already says the slug comes from search_products. The description adds nothing about the slug or its source, so the baseline 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 conveys that the tool yields two links (order link and sample link) for a garment, which lets an agent infer the general purpose. However, it never states plainly 'returns URLs' with a verb+resource framing; it describes output obliquely as 'The link that takes the customer...'. Sibling tools like get_quote and get_product are not differentiated.

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?

'Give these to the customer; nothing is ordered until they finish it' implies when to use it (customer wants to proceed to order or sample) and clarifies no order is placed. There is no explicit when-not or guidance on choosing between the order link and the sample link vs. other tools like get_quote.

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