Market Category Booster

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

With no annotations, the description carries the full burden and does so well. It discloses that the taxonomy is walked one level at a time, that results include reasons per match, that truncation is signaled with `truncated: true`, and that missing authentication/payment yields payment requirements instead of a result.

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 the core purpose, followed by behavioral details and billing implications. Every sentence provides necessary information with no filler or redundancy.

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 description covers the operation, output format, truncation edge case, billing behavior, and authentication requirements. Given the output schema exists and both parameters are fully documented in the schema, this is complete enough for an agent to invoke the tool correctly.

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 baseline is 3. The description does not add significant meaning beyond the schema: it repeats that the input is a free-text product description and that store_id refers to a marketplace, but the schema already conveys this.

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 ('Map') and names both the input (free-text product description) and the output (marketplace category path). It clearly distinguishes itself from siblings like list_stores and payment_info by stating its unique operation.

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 explicitly tells when to use the tool: 'Use it to assign a listing category to a product you only have prose for.' It does not explicitly list exclusion criteria or alternatives, but this usage context is clear enough for an agent to select it appropriately.

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 the full burden and does disclose important behavior: the call is free of charge on purpose and the list only includes marketplaces with loaded taxonomies. It does not cover auth or rate limits, but for a simple read-only, zero-parameter list that is reasonable.

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 short and front-loaded: the first paragraph states the core function, and the second adds a purposeful, non-fluffy justification. Every sentence earns its place and there is no redundancy.

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 tool with an output schema, the description covers what it does, why it exists, and when to call it. The relationship to `categorize_product` and the free-of-charge behavior are important contextual details that are fully covered.

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 has zero parameters, so the description has nothing to clarify about inputs. The baseline for 0 params is 4, and the description indirectly reinforces that the output values are the valid inputs for `categorize_product`'s `store_id` parameter, which adds useful semantic context.

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 ('List') and resource ('marketplaces whose taxonomies are loaded'), and explicitly frames the output as the accepted `store_id` values for the sibling `categorize_product`. This clearly distinguishes it from the other siblings without needing to open the schema.

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 explicitly tells agents to use this tool to discover the valid `store_id` values before calling `categorize_product`, and explains the rationale is to avoid the cost of a failed paid call. This is a clear when-to-use statement that also names the specific sibling it supports.

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 discloses that the tool is 'free of charge', does not require an API key, and returns specific fields as JSON. It also explains the intended use for signing authorization. While it does not explicitly state read-only semantics, the nature of the tool implies it, making this a solid disclosure.

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 three sentences long, front-loads the core action, and provides necessary context without fluff. Each sentence contributes value—purpose, target user, return content, and sequencing—making it highly 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?

Given that there are no parameters, an output schema exists (though not shown), and the description covers the tool's purpose, target user, return content, and usage sequencing, it is complete for an agent to use this tool correctly. Nothing essential 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 are zero parameters, so the description correctly omits any parameter details. The schema coverage is 100% by triviality, and the baseline for zero parameters is 4. The description adds no unnecessary parameter information, which 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 states a specific action ('Return the x402 payment requirements') and a specific context ('for one categorization call'), clearly identifying the tool's purpose. It references the sibling `categorize_product`, distinguishing itself as a prerequisite step, and implicitly separates from `list_stores` by focusing on payment 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?

It explicitly states the intended user ('an agent that holds no API key') and the usage sequence ('before calling `categorize_product`'). This provides clear, actionable guidance on when to use this tool and how it integrates into a workflow, with no ambiguity.

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