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

With no annotations provided, the description carries the full disclosure burden, and it delivers: it states that value is rounded up to the next €100, enumerates the four outputs, discloses the 20% provisional payment rule, and notes that missing inputs fall back to documented defaults. This is substantial behavioral context for a pure calculation tool, though it stops short of describing the response format 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?

The description is compact, action-first, and organized as a clear list of outputs followed by a compact defaults note. It earns a 4 rather than 5 because of the redundant 'calculator calculator' typo, which is a minor polish defect in an otherwise tightly written definition.

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 two-parameter tool with a fully documented schema and no output schema, the description is reasonably complete: it names the inputs' roles, enumerates all outputs, and discloses key calculation behaviors. The main gaps are the absence of an explicit response shape and the lack of guidance on which sibling to use for related but different needs.

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; both 'basis' and 'value' are already well documented in the schema. The description adds a small amount of parameter-relevant context by stating that missing inputs fall back to documented defaults and by implying the rounding rule applies to the value, but it does not deeply expand parameter meaning beyond what the schema provides.

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 verb ('Run') and a specific resource (the Malta stamp duty calculator), and it lists the computed outputs (value taken for duty, duty payable, effective rate, provisional payment), which makes the purpose concrete. However, it does not explicitly differentiate itself from the sibling calculator_describe; the distinction is implied by the word 'Run' versus 'describe' rather than stated.

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 this tool is the one that executes the stamp duty calculation, and the sibling names (calculator_describe, enquiry_describe, enquiry_fields, submit_enquiry) suggest there are alternatives for describing or submitting enquiries. However, there is no explicit when-to-use versus when-not-to-use guidance, and no sibling is named as an alternative.

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 provided, the description carries the burden of explaining behavior. It clearly indicates that this is an informational/descriptive tool returning documentation-style content rather than performing calculations. It does not explicitly say 'does not calculate,' but the wording strongly implies it.

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 efficiently enumerates the tool's coverage: inputs, outputs, assumptions, and tables. There is no filler or redundancy, and the core purpose 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 zero-parameter describe tool with no output schema, the description gives sufficient context about what content the tool will return. The only gap is that it does not explain its workflow placement relative to sibling tools, such as suggesting to call it before calculate.

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 and 100% schema coverage, so no parameter documentation is needed. The description appropriately focuses on the calculator's conceptual inputs rather than MCP invocation parameters, meeting the baseline for a parameterless tool.

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 what the tool does: it describes the inputs, outputs, assumptions, and tables of the Malta stamp duty calculator. This distinguishes it from the calculate sibling, which presumably performs the calculation, though it does not explicitly name the alternative.

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 use case is implied: call this tool to learn about calculator inputs, outputs, and underlying assumptions before calculating. However, it does not explicitly state when to prefer this over calculate or explain its relationship to enquiry_describe, leaving some room for 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?

With no annotations, the description carries the full transparency burden and meets it: it states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and that the tool returns details about recipients, consent wording, and confirmation. This gives an agent a clear safety and expectations profile without needing 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 compact and front-loaded: 'Read first' signals priority, then the main purpose, key caveats, and return contents are each given in a single lean sentence. Every phrase adds value 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 description tool with no output schema, the description is complete: it explains what the tool reveals about submit_enquiry, the non-purchase/non-guarantee nature of the enquiry, and exactly what information is returned. No important gap remains for an agent to invoke it 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?

The tool has zero parameters and 100% schema coverage, so the baseline is 4. There are no parameter semantics to document, and the description correctly focuses on output and behavior instead.

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 opens with 'Read first' and explicitly says the tool 'States plainly what submit_enquiry does', naming the exact verb, resource, and domain (Malta Stamp Duty). It is clearly distinguishable from sibling tools: it describes the submission workflow rather than performing it, and the title reinforces the outcome of an enquiry.

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?

'Read first' provides a clear contextual cue to use this tool before submit_enquiry, and the description explains the enquiry process so an agent can decide whether submitting is appropriate. It does not explicitly enumerate when-not-to-use scenarios or name alternative tools beyond submit_enquiry, so it stops short of a 5.

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 provided, the description carries the burden of behavioral disclosure. It transparently lists what data is provided, including 'help text and the allowed options where there are any,' which gives useful detail. However, it never explicitly states the tool is read-only, has no side effects, or what the exact return shape is beyond the attribute list.

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 concise sentences with no filler. The core information about what the tool returns is front-loaded, followed by a practical usage note. Every clause earns its place.

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 no annotations and no output schema, the description is complete enough for an agent to understand what this tool returns, what each field contains, and how to chain it with submit_enquiry. The attribute list (key, label, type, required, help text, allowed options) fully compensates for the missing output schema.

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 has zero properties, so there are no parameters to document. The baseline for zero parameters is 4, and the description adds useful semantic information by explaining how the returned field keys are used in submit_enquiry, even though this relates to output rather than input.

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 exactly what the tool returns: 'Every field of the Malta Stamp Duty enquiry' with an explicit list of attributes (key, label, type, required, help text, allowed options). This is a specific verb+resource that distinguishes it from sibling tools like submit_enquiry (which consumes answers) and enquiry_describe (which likely describes the enquiry as a whole).

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 clear context by telling the agent to 'Pass answers to submit_enquiry keyed by field key,' which directly connects this tool to its sibling workflow. It doesn't explicitly exclude alternatives like enquiry_describe, but the purpose is clear enough that an agent can infer when to use this over the other siblings.

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 succeeds: it discloses the two-step validation and submission flow, the requirement to show the person the summary and consent line, the need for a confirmation token, and that a provider sees nothing until the person clicks an email link. It also explains the exact meaning of consent.

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 longer than average but every sentence earns its place, covering purpose, exclusions, a two-step procedure, and the quoted consent text. It is front-loaded with the core action and what it is not, and the steps are clearly labeled.

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 sensitive two-step tool with human providers and no output schema, this description is remarkably complete. It explains the full workflow, the consent gate, the confirmation token handoff, and the email-link privacy step, leaving no obvious gap that an agent needs to guess before calling it 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 coverage is 100% and already documents answers, consent, and confirmation. The description adds value by explaining how they interlock: answers are keyed by enquiry_fields, consent must be true, and confirmation is the Step 1 token reused in Step 2. This goes beyond the schema's isolated parameter 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 uses a specific verb and resource ('Submits an enquiry to Malta Stamp Duty') and immediately clarifies what it is not ('NOT a purchase, NOT a guaranteed quote'). This clearly distinguishes submit_enquiry from the sibling calculate and describe tools without needing to open schemas.

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 clear when-to-use guidance: it is for submitting an enquiry after gathering answers, in a two-step process with explicit conditions for Step 1 and Step 2. It also gives a when-not hint ('NOT a purchase, NOT a guaranteed quote'), though it does not explicitly name sibling alternatives like enquiry_describe.

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