Coreplex

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

Annotations already declare readOnly/destructive=false and openWorldHint=false, so the safety profile is covered. The description adds behavioral context beyond that: results are limited to the exact item match and 'similar listings kept apart,' telling the agent what is intentionally filtered out of the response. It does not discuss rate limits or freshness, but with annotations and an output schema present the bar is lower.

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?

Three tightly packed sentences: scope first, then parameter guidance, then an example. Every element is used and front-loaded, though the opening fragment is dense and slightly telegraphic compared to plain prose.

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?

With only two parameters, full schema coverage, annotations, and an output schema, the description covers what is needed to call it correctly and what the results represent. Minor omissions (freshness or latency of seller data) are not essential for invocation.

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 baseline is 3, but the description goes further by explaining the alternative ?variant= URL form for multi-option products and pairing it with a worked example, which clarifies when variant_id matters. That is genuine added meaning over the schema's terse 'Option to price' field.

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 operation and scope: it returns other sellers of the exact same item (matched by catalog ID or barcode), scoped to one variant, with similar-but-unrelated listings deliberately excluded. That is precise enough to separate it from search_products or get_product, though it never explicitly contrasts itself with those siblings by name beyond citing get_product as a variant_id source.

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 gives a clear condition for the optional parameter ('Pass variant_id ... or a ?variant= URL for multi-option products') and shows a concrete call example, which tells the agent when variant_id is needed. It stops short of stating when not to use this tool versus search_products, so it is clear context without explicit exclusions.

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, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds one genuinely useful behavioral nuance: claims are 'seller-stated,' i.e. self-reported rather than verified, which affects how much the agent should trust the filter. No pagination or result-shape detail beyond that.

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, front-loaded with the resource and filter dimension, followed by a compact concrete example. No filler.

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?

Output schema exists so return values need not be explained, and annotations carry the safety profile. The description covers resource, filter semantics, and an example, leaving only sibling routing (search_products) unaddressed.

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 filter/enum, query, and limit are already documented; baseline is 3. The description expands the enum acronyms into readable claim names and the example demonstrates filter+query combining, a modest add over 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?

States the resource (health products) and the distinguishing axis (seller-stated claim), with an explicit value list. It separates itself conceptually from search_products and list_brands, though the verb 'find' and the boundary with search_products is only implied.

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 claim-based framing implies when to use it, and the example call shows a typical invocation. But there is no explicit when-to-use guidance and no mention of the alternative search_products for non-claim browsing.

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 annotations already cover the safety profile: read-only, non-destructive, and not open-world. The description adds useful behavioral context by explaining that results include match classifications and evidence, but it does not discuss catalog scope, result limits, or other operational 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 compact and includes a concrete example, with little wasted text. It is somewhat fragmentary and does not front-load a clear action verb, which keeps it from a 5.

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 input schema is simple and fully documented, the output schema exists, and annotations cover safety. However, the description does not fully resolve what a 'product passport' is relative to sibling tools, leaving some selection ambiguity for an agent.

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% and the single product_url parameter is already documented as a Shopify product URL. The description adds an example URL, which is mildly helpful, but does not add substantive semantics 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 clearly indicates the tool returns the brand's own listing plus matching store listings from a catalog search, labeled as same, likely same, or not same with evidence. It does not explicitly differentiate this behavior from siblings such as compare_prices or get_product, which keeps it from a 5.

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 is used to find matching store listings for a product URL, but it gives no explicit when-to-use guidance, no exclusions, and no comparison to alternatives like compare_prices or get_product.

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 content shape of the response (policy links, official-store flag), but since an output schema already exists, that field enumeration is largely redundant rather than new behavioral context. No mention of auth, rate limits, or error 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?

Two compact sentences: the payload summary comes first, the example second, with no filler. It reads as a terse fragment rather than a full sentence, but every element earns its place and nothing is buried.

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 tool with an output schema, the description covers what is returned and gives a usable example. The only meaningful gap is the absence of when-to-use guidance relative to search_products and compare_prices, which keeps it from a 5.

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 there is only one parameter, so the schema does the heavy lifting; baseline is 3. The description contributes a concrete example value that illustrates the URL format, and the schema notes the 'seller_url' alias, but no additional semantics (e.g., how to obtain the URL, what happens on invalid input) are added.

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 the resource (one product listing) and enumerates the payload an agent gets back: price per option, stock, seller, official-store flag, and policy links. The implied verb 'get' is clear from the name, and 'One listing' distinguishes it from search_products or compare_prices. It stops short of explicitly naming those siblings, so it isn't a 5.

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 phrase 'One listing' implies a single-product lookup as opposed to a search or comparison, and the example URL shows the expected input shape. However, it never states when to prefer this over search_products, compare_prices, or get_passport, so the routing guidance is only implied.

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 the safe read-only, closed-world profile, so the safety burden is covered. The description adds that each field comes with 'the policy's exact sentence', a useful note about response fidelity, but the output schema already covers return shape, so added value is modest.

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 sentence plus a compact example, with the returned fields front-loaded. No filler. The example earns its place by showing the exact expected input shape.

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?

With annotations covering the safety profile and an output schema defining return values, the agent has what it needs to call this correctly. The description need not expand return format or edge cases, so its brevity is not a real 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 a single documented required parameter, so the baseline is 3. The inline example supplies a concrete value shape but otherwise repeats what the schema already states.

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?

States a specific verb+resource ('Seller's return terms') and enumerates what is returned (window, condition, opened items, return shipping). It is immediately distinct from all siblings, which are product/price/brand tools. No explicit sibling differentiation, but the resource is 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?

Usage is only implied – an agent infers this is the tool for return-policy questions. There is no statement of when-not to use it or how it relates to siblings like get_product. Acceptable but leaves routing to inference.

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 readOnly, non-destructive, and closed-world, so safety is covered. The description adds real context by scoping results to brands with a confirmed official store, which is a non-obvious filtering behavior. It says nothing about pagination, result size, or ordering, and the output schema covers the return shape.

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 sentence plus a compact example; the scope qualifier is front-loaded before the optional filter. The example is slightly redundant given a fully documented enum but costs little.

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-required-parameter listing tool with a fully described schema and an output schema, the description covers what is needed to call it correctly. Only the routing against sibling product tools and any result-size behavior are 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 description coverage is 100% and the single category parameter carries an enum, so the schema does the heavy lifting. The example {"category":"beauty"} illustrates invocation but adds no semantics beyond what the schema already states.

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 the resource (brands) and a meaningful qualifier ('confirmed official Shopify store'), plus the optional category filter. It is clear what the tool returns, though it never explicitly contrasts itself with product-oriented siblings like search_products.

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: list brands, optionally narrowed by category. There is no explicit when-to-use guidance, no statement of when to prefer this over search_products or compare_prices, and no prerequisites or exclusions.

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 that returned results include seller names and an official-store flag, which is modest but real context beyond the structured fields; nothing is said about scope limits of the 'Shopify brands' corpus.

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 compact sentence plus a single illustrative call, with the core purpose front-loaded. The example earns its place by demonstrating shape, though the seller/official-store clause borders on return-value detail already covered by the output schema.

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?

With annotations covering safety, a 100%-covered schema, and an output schema that documents returns, the description is nearly sufficient. The main gap is routing context: nothing explains how this differs in scope from get_product or compare_prices.

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 all three parameters are already documented, establishing a baseline of 3. The embedded example shows query and limit used together, which is a small addition but does not clarify official_only or search matching semantics.

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?

States a specific verb and resource ('Find products from Shopify brands') and adds a distinguishing output trait (results name the seller and flag official stores). It does not explicitly contrast with siblings like get_product or compare_prices, so it falls short of a 5.

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 search framing and the note that results identify sellers/official stores, which hints at the discovery use case. However, there is no explicit when-to-use, when-not-to-use, or named alternative among the six sibling tools.

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