brands

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

No annotations provided. Description only lists returned fields; lacks disclosure of side effects, authentication needs, rate limits, or pagination behavior. For a read tool, minimal 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?

Single sentence front-loads purpose and lists return fields with no wasted words. Clear and efficient.

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?

No output schema; description mentions some fields but not all possible ones. For a 'full profile' tool, listing fields adds value but could be more explicit. Adequate for a simple tool.

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 schema already describes parameter (id_or_alias) with example values. Description does not add new parameter meaning beyond schema, so baseline 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?

Description clearly states action 'Get' and resource 'full profile for a specific brand', lists specific fields (categories, website, headquarters country, description). Distinguishes from siblings like get_brand_retailers by focusing on brand profile data.

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 explicit guidance on when to use this vs. other tools like get_brands or get_brand_retailers. Implies single brand lookup but does not provide context on prerequisites or 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?

With no annotations, the description carries full burden. It discloses sorting order and the 'seal_implemented' field, but does not mention read-only behavior, authentication, or error scenarios. Adequate for a simple GET 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?

The description is a single, well-structured sentence that front-loads the action and resource. It is concise yet informative, though slightly long.

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 lacking an output schema, the description conveys the return format (list sorted by plan, with seal_implemented). It covers the essential information for a simple list tool with one required parameter.

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 single parameter 'id_or_alias' is fully described in the schema (100% coverage). The description adds no additional parameter-level information, meeting the baseline.

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 action ('Get all retailers authorized by a brand') and the resource, specifying sorting order and included field. This distinguishes it from sibling tools like get_brand or get_retailer_brands.

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 clearly indicates when to use this tool (to get retailers for a specific brand with sorting). It does not explicitly exclude alternatives, but the name and context make it evident.

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?

Since no annotations are provided, the description fully discloses the return fields (brand names, slugs, logos, authorized-retailer counts) and the effect of the search parameter. It does not mention rate limits or authentication, but for a read-only list tool, the provided transparency is adequate.

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, front-loading the purpose and adding a key usage hint. Every sentence is essential, with no redundant 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 (3 optional parameters, no nested objects, no output schema), the description explains the core functionality and return content. It is complete enough for an AI agent to select and invoke correctly, though pagination details are more implied than explicit.

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?

With 100% schema description coverage, the baseline is 3. The description adds value by explaining that the 'search' parameter filters by brand name or alias, and that omitting it returns the full index, which is not evident from the schema alone.

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 specifies a clear action ('Search authorized brands and manufacturers') and resource ('authorized.by'), and distinguishes from siblings by mentioning it returns a list with brand names, slugs, logos, and retailer counts, contrasting with get_brand for a single brand.

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 that omitting the 'search' parameter retrieves the full index, clarifying when to use the search option. However, it does not explicitly state when to use this tool over siblings like get_brand or get_brand_retailers.

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 provided. The description indicates a read operation ('Get') but does not explicitly confirm no side effects, permissions, rate limits, or error behavior. The absence of annotations places burden on description, which is insufficient.

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 sentence that efficiently conveys purpose and output fields. It is front-loaded with the core action. Could be slightly improved with bullet points for readability, but overall concise.

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 no output schema, the description lists many output fields (address, hours, categories, etc.) and explains 'seal_implemented'. It covers the main profile aspects but omits edge cases like missing retailer or response structure.

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 baseline is 3. The description adds 'Retailer numeric ID or alias', which aligns with the schema description but does not add further meaning (e.g., format constraints or examples).

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 retrieves the full profile for a specific retailer and lists the included fields (address, contact details, etc.). It distinguishes itself from siblings like get_retailers (plural) and get_brand_retailers.

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 use for a single retailer but does not explicitly state when to use this tool versus alternatives like get_retailers or get_brand_retailers. No prerequisites or error handling 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?

No annotations are provided, so the description carries full burden. It discloses that results are sorted by brand name and includes partnership_date, making behavior transparent. It does not mention pagination or limits, but for a simple list tool this is adequate.

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 concise sentences with no wasted words. The key information (action, resource, sorting, field) is front-loaded.

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 simple single-parameter tool with no output schema, the description sufficiently explains the return value (all authorized brands, sorted, with partnership_date). No missing critical information.

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 parameter 'id_or_alias' described as 'Retailer numeric ID or alias.' The description repeats the requirement implicitly but adds no new semantic information beyond what the schema provides. 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 uses a specific verb 'Get' with resource 'brands a retailer is authorized to sell' and includes sorting and additional field 'partnership_date'. It clearly distinguishes from sibling tools like get_brand_retailers (retailers for a brand) and get_brand (single brand).

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 is clear about what the tool does (retrieves authorized brands for a retailer) but does not explicitly state when to use it versus alternatives. However, the sibling tool names provide context, making the intended usage inferable.

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 exist, so the description carries the full burden. It discloses return fields and the platform. It does not mention pagination behavior, rate limits, authentication, or that it is a read-only operation. While it provides useful output context, it lacks some behavioral details that would help an agent plan calls.

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 filler. The first cover purpose and outputs, the second gives a concise usage instruction. Every part adds 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?

Given three well-documented parameters, no output schema, and sibling tools, the description sufficiently covers core functionality and key usage. It lacks details on result ordering, error handling, or limits, but remains adequate for typical agent usage.

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 individual parameter descriptions. The description adds value by explaining that omitting 'search' retrieves the full index, which clarifies the parameter's role. It also lists returned fields, indirectly helping understand parameter effects.

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 explicitly states the verb 'Search' and the resource 'authorized retailers (shops) on authorized.by'. It lists specific return fields (names, slugs, URLs, logos, counts, seal_implemented) and contrasts with the full index variant. This clearly distinguishes it from sibling tools like get_retailer (singular) and get_brand_retailers.

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 notes when to use it ('search' filter) and provides the tip to omit 'search' for the full index. However, it does not explicitly recommend against using it when a single retailer is needed (suggest get_retailer) or mention when other sibling tools are more appropriate.

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