Channel3 Shopping

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

Annotations already establish readOnly, idempotent, and non-destructive behavior, so the description does not need to restate safety traits. It adds the behavioral context that the tool provides search and pagination, but it does not expound on pagination mechanics or any edge-case behavior such as required page_tokens or lack of filtering capabilities.

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 with no filler. It is appropriately short for a high-level tool summary, though it may be too sparse to carry the full guidance burden for six parameters and a roster of sibling tools.

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?

Despite having six parameters, an output schema, and five closely related sibling products, the description provides only one sentence of behavior. The agent has no information about parameter roles, when to page overseers, product types, or how this tool relates to search_products, making the description insufficient given the tool's complexity.

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 only 50%, and the remaining parameters such as device_id, image_url, and limit have no description in the schema. The tool description simply says search and pagine; it does not compensate for the incomplete parameter documentation by explaining how these arguments interact with search or browsing.

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 action ('Search and page through products') and a clear resource ('products for the storefront UI'). It stops short of distinguishing itself from sibling tools like search_products or get_products, so it does not fully earn the top score.

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 gives a broad context ('storefront UI') but does not say when this tool should be used instead of search_products, get_products, or other siblings. There are no exclusions, alternatives, or conditions provided, so the agent is left guessing which tool fits a given request.

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 and context signal explicitly disclose that offers are resolved in real time and should not be cached, which is critical behavioral information not visible in annotations. The idempotenceHint and readOnlyHint are present and not contradicted. The fact that product_id alone may not uniquely identify a product is disclosed in the param context, adding transparency.

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 extremely concise (one sentence) and directly to the point without any fluff. Every word adds meaningful information: 'Fetch' = action, 'product' = resource, 'with live offers' = key behavior, 'for the storefront UI' = usage context. It is properly front-loaded with the core behavior first.

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 read-only, idempotent fetch tool, the context signal and parameter explanations cover the main gaps: the real-time nature of offers, optionality of thread_id/device_id, and the uniqueness limitation of product_id. The output schema fully specifies the return structure, so no explanation of return values is needed. However, sibling differentiation is not robustly given, leaving some ambiguity about when to choose this tool vs get_product.

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 covers 100% of parameters with descriptions for product_id and selected_options, but thread_id and device_id have no parameter descriptions, leaving them undocumented in the schema. The used context signal fills in the gap by explaining that thread_id/device_id are optional, only for context, and normally passed together, and that selected_options re-resolves offers. This adds value beyond the schema and compensates for the missing descriptions.

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 'Fetch a product with live offers, for the storefront UI' clearly states the verb ('fetch'), the resource ('product'), and the distinguishing feature ('live offers'). However, it does not explicitly differentiate from sibling tools like get_product or list_offers, though the live-offers and storefront context provide partial differentiation.

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 explains the primary use case ('for the storefront UI') and the context signal clarifies that it is used directly from the storefront/product UI. It does not explicitly state when to avoid using it or compare with alternatives like list_offers or search_fish, but the differentiation from list_offers is implied by 'live offers' vs listing. The context signal also adds a valuable note about not caching, reinforcing the intended usage.

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 declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the 30-day window and storefront context, which is useful but limited; it does not explain behavior around variant resolution or filtered results beyond that. This is a modest improvement over the annotations.

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 one effective, front-loaded sentence with no filler. It states the core functionality and intended context without redundant detail, making it easy to scan and parse.

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 read-only lookup tool backed by an output schema and active annotations, the description is mostly sufficient, but it lacks any signposting for how this tool compares to siblings and leaves some parameter behavior muddy. The core call is clear, but the surrounding decision of when to use it is omitted.

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 only 50%, and the description does not explain any of the parameters directly. It references 'product' which maps to product_id, but leaves device_id, thread_id, and selected_options completely unexplained, so an agent cannot infer their purpose beyond the schema's partial doc.

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 specific verb—Fetch—and the resource: a 30-day price history for a product, with a context qualifier ('storefront UI'). This clearly differentiates the tool from siblings like search_products or get_details, which serve other purposes. The operation 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?

There is no explicit guidance about when to use this tool versus the sibling product tools, and no mention of prerequisites or when not to use it. The phrase 'for the storefront UI' hints at a context but does not direct the agent toward this tool over 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?

Annotations already mark the tool as read-only/idempotent, and the description adds critical behavioral context: results are returned in the storefront UI, and the thread_id must be propagated unchanged to every subsequent Channel3 call, including unrelated searches. This goes beyond annotations and is essential for correct stateful usage.

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 front-loaded with purpose and usage, and the key behavioral details are present. However, the final two sentences about thread_id largely repeat information already in the schema's thread_id parameter description, adding redundancy that could be trimmed without losing necessary emphasis.

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 simple two-parameter tool with an output schema present, the description covers purpose, usage, and the critical thread_id statefulness rule. It does not need to explain return values due to the output schema, and the context is sufficient for correct 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 coverage is 100% for both parameters, so the baseline is 3. The description adds meaning by clarifying that product_ids can be IDs from search results or retailer URLs, and that multiple IDs are fetched in parallel for comparison, which enriches the schema's bare field descriptions.

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 action ('Get full product data') with a defined resource (offers, description, attributes, images) and identifies two input methods (product ID or retailer URL). It distinguishes itself from siblings by explicitly referencing search_products and noting batch comparison, 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 provides explicit guidance to use search_products to find products first and suggests passing multiple IDs for comparison. However, it does not clarify when to prefer get_products over sibling tools like get_details or get_similar, so it lacks full exclusions or alternative scenarios.

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, idempotidHint, and destructiveHint=false, so the core safety profile is covered upstream. The description adds no additional behavioral facts such as session requirements, rate limits, what is not returned, or the meaning of device_id/thread_id; it simply adds the storefront context.

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 exactly one concise sentence with a front-loaded action ('Find products similar...') and no filler. Every word serves the intent and it is 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 the existence of four input parameters, no output schema, and minimal parameter-level documentation, the description is incomplete for the agent. It does not clarify how limit, device_id, and thread_id affect results, nor what the response contains, so a caller must guess at essential calling semantics.

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 low: only product_id has a schema description, and the tool description does not explain limit, device_id, or thread_id. Since explanation must compensate for this 25% coverage, the description falls short an agent cannot infer the purpose of device_id and thread_id.

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 clear verb ('find') and a clear resource ('products similar to a given product') with a deployment context ('for the storefront UI'). It does not explicitly name the sibling get_customer_details, but the resource is distinct enough that an agent would not confuse the two.

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 'for the storefront UI' gives general context for when the tool is relevant, but there is no explicit guidance about when to use it versus get_customer_details or when not to use it. The usage context is implied rather than spelled out.

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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses critical behavior: result cap ('up to 8 product cards') and the mandatory thread_id propagation ('You MUST include it unchanged on every subsequent Channel3 tool call'). This is significant stateful context.

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?

Four sentences, each with a clear purpose: purpose, batching/query guidance, return shape, and mandatory thread_id rule. The thread_id warning is repeated for emphasis, which is justified given its importance. Slightly verbose but well-structured.

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 output schema and annotations, the description covers the essential aspects: purpose, usage pattern, return size, and the cross-call state requirement. No critical information 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%, so a baseline of 3 applies. The description adds value by instructing to put constraints in query and reinforcing the thread_id rule, which helps the agent use parameters correctly beyond the schema text.

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 function: 'Search 100M+ products across thousands of retailers for one product type.' This is a specific verb+resource+scope that distinguishes it from siblings like browse_products or get_details.

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?

Provides explicit usage guidance: 'Call once for each distinct product type, and send independent calls together' and 'Put relevant constraints in query.' It also specifies the thread_id propagation requirement. It does not explicitly name alternative tools, but the intended use case is clear.

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