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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the tool's function (providing advice) without revealing what the advice looks like, whether it is deterministic, whether it returns a ranked list or plain text, or any other execution traits. For a tool with no annotations, this is a notable 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?

The description is a single, well-structured sentence with no filler. It front-loads the core purpose and includes the key marketplaces without verbosity, making it appropriately sized for the tool's simplicity.

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 low complexity (one parameter, no output schema, no annotations), the description is adequate but not rich. It tells what the tool does and the input it expects, but does not specify the format or granularity of the advice, which an agent might need to know to use it effectively. Without annotations, it could compensate by briefly describing the output.

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 already has full documentation for the single 'tier' parameter (100% coverage), so the baseline is 3. The description adds that the advice is 'tailored', implying the tier affects the output, but it does not elaborate on how tier values map to advice specifics beyond the schema's allowed values.

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 verb ('provides') and resource ('tailored marketplace distribution advice') and names the exact marketplaces covered. It implies a distinction from the sibling 'quick_appraise' (appraisal vs. listing strategy), though it does not explicitly contrast them.

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 on when to use this tool versus the sibling 'quick_appraise', nor any exclusions or prerequisites. The usage context ('when you need distribution advice') is only implied by the tool's name and description, and no alternative tool is 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 the full burden of behavioral disclosure. It mentions 'instantaneous' and the value bands, but it does not disclose whether the operation has side effects, whether it uses live market data, or any access or rate considerations. For a tool with no annotations, this is a meaningful 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?

The description is a single, well-structured sentence that front-loads the core purpose and includes the key output detail of value bands. There is no wasted wording or 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?

For a simple tool with one fully documented parameter and no output schema, the description gives enough information: the agent knows the input domain and the output consists of three value bands. It could be more explicit about output format or data source, but overall it is adequate 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 description coverage is 100%, and the schema already fully describes the only parameter ('domain') as 'The domain name to appraise'. The tool description adds no additional parameter meaning beyond what the schema provides, so the baseline score 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 uses a specific verb ('Performs') and identifies the resource ('domain appraisal') with concrete output details (retail, wholesale, quick-liquidation value bands). This clearly distinguishes it from the sibling get_listing_strategy, which would focus on listing approach rather than valuation.

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 makes clear the tool is for obtaining an appraisal of a domain, which is a distinct use case from get_listing_strategy. It does not explicitly state when not to use it or name the alternative, but the context is unambiguous enough for an agent to select it for valuation tasks.

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