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

With no annotations, the description must carry the behavioral disclosure burden. It does add one useful behavior: 'Missing inputs fall back to their documented defaults.' However, it does not clarify whether the listed phrases are outputs, inputs, or calculation rules, nor does it describe the return format or any side effects. The lack of clarity around 'Deemed domiciled in Cyprus (1 = yes)' weakens the 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 short and front-loaded with the action, which is good. However, the 'calculator calculator' typo and the unlabeled semicolon list ('SDC rate on your dividends; Deemed domiciled in Cyprus...') make it feel disorganized and reduce clarity. It is concise but not as well structured as it could be.

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?

This tool has four parameters, no annotations, and no output schema, so the description needed to explain what the calculator returns and how to interpret the results. It only provides a default-fallback note and a confusing list of calculator-related phrases. An agent would not know whether the output is a rate, an amount, or a breakdown, making the description incomplete for reliable 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%, so the baseline is 3; all four parameters have descriptions, defaults, and ranges. The description adds some domain context by mentioning 'SDC rate', 'SDC on dividends', and 'SDC on interest', but it does not clearly map these concepts to specific parameters. It therefore provides only marginal value beyond the schema.

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 and resource: 'Run the Cyprus non-dom SDC calculator calculator'. The title and opening phrase make the tool's core purpose clear, even though the word 'calculator' is duplicated and the semicolon list is ambiguous. It does not explicitly distinguish the tool from its siblings like calculator_describe, so it misses 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?

No explicit guidance is given about when to use this tool versus alternatives such as calculator_describe or submit_enquiry. The only usage-related note is that missing inputs fall back to defaults, which is more of a behavioral hint than a usage guideline. An agent is left to infer the appropriate context.

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. It transparently states the tool returns documentation about inputs, outputs, assumptions, and tables, and by nature is a read-only describe operation. It could be more explicit that it performs no calculation, but the description does not hide or misrepresent 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?

A single sentence that front-loads the content scope and wastes no words. Every clause adds meaningful information about what the documentation tool covers.

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 adequately conveys what an agent will receive: inputs with units/ranges/defaults, outputs, assumptions, and tables. It is complete enough for selection and invocation, though it does not enumerate the actual calculator inputs or outputs, which is acceptable for a meta-description 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?

The tool accepts zero parameters, so the empty schema is fully covered and there is nothing for the description to explain. The baseline for zero-parameter tools is 4, and the description appropriately clarifies that it describes the calculator's inputs rather than taking its own.

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 identifies the tool as a documentation/description tool for the Cyprus non-dom SDC calculator, specifying exactly what it covers: inputs, outputs, assumptions, and tables. This distinguishes it from sibling tools like calculate, which presumably performs the calculation.

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 context is clear: an agent should use this tool to understand the calculator's inputs, outputs, and underlying assumptions, likely before or instead of invoking calculate. It does not explicitly state exclusions or when-not-to-use, but the purpose is unambiguous enough for correct selection.

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 behavioral burden and handles it well: it discloses that this is free, involves no purchase or payment, guarantees no quote, and explains what the returned content includes. This gives the agent accurate expectations beyond the tool name alone.

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 four efficient sentences, front-loaded with 'Read first' and then plainly stating outcomes and exclusions. Every sentence adds value, and there is no redundant restatement of the title or tool name.

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 explanatory tool with no output schema, the description is fully adequate: it says what the tool explains, what the user will not get, and what the returned content covers. It also orients the agent among siblings by contrasting with submit_enquiry.

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 by triviality, so there are no parameter semantics to document. As the rubric sets a baseline of 4 for zero-parameter tools, nothing additional is needed in the description.

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 ('states', 'returns') and resource ('what submit_enquiry does on Cyprus Non-Dom Calculator'), making clear this is an explanatory tool rather than the action tool itself. It is immediately distinguishable from submit_enquiry, which performs the action.

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 opening 'Read first' explicitly signals when to use this tool: before acting on submit_enquiry. It gives clear context about the enquiry flow and what to expect, though it does not explicitly enumerate alternatives or state when not to use the tool.

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 it clearly discloses the return payload contents. It also communicates a behavioral relationship: the output is meant to feed submit_enquiry. Since this is a read-only metadata listing, the lack of side-effect discussion is acceptable.

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 with no wasted words. The core enumeration of returned attributes is front-loaded, and the usage note follows in a compact second sentence.

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 metadata listing with no output schema, the description provides enough information to know exactly what will be returned and how to apply it. It omits error handling or authentication details, but those are not expected for this simple query-like 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?

The tool takes no parameters, so the schema is trivially fully covered and no parameter documentation is needed. The description adds useful context about how the returned data should be used, which is the relevant semantic content. A baseline of 4 is appropriate for a zero-parameter 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 states the tool returns every field of the Cyprus Non-Dom Calculator enquiry and enumerates the exact attributes: key, label, type, required, help text, and allowed options. It also distinguishes itself from sibling submit_enquiry by noting that answers are passed there keyed by field key. Though it lacks an explicit imperative verb, the resource and scope are 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?

It clearly connects to submit_enquiry by explaining that the returned field keys are the keys to use for answers. This gives an explicit workflow context for when this tool is useful. However, it does not explicitly contrast with sibling tools like enquiry_describe or calculator_describe, so the exclusion guidance is not fully stated.

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 behavioral burden and does so: it discloses the side effects (enquiry submitted, email with a click-through link, details shared with up to three providers who contact the person directly), the gating condition (no provider sees it before the person clicks), and the exact meaning of consent. This is far beyond what the schema conveys.

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 operationally critical distinction ('NOT a purchase, NOT a guaranteed quote') is front-loaded, and the two steps are cleanly ordered. The block is dense and the verbatim consent sentence is long, but that text is required for the consent parameter to be meaningful, so most of the length 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?

There is no output schema, so the description compensates by naming the step 1 return values (summary, consent line, confirmation token) and the step 2 outcome (submission plus a click-to-confirm email). For a nested-parameter, two-phase tool with no annotations, this is complete enough 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%, so the baseline would be 3, but the description adds sequencing semantics the schema cannot express: answers are keyed by field key from enquiry_fields, consent must be true, and the confirmation token is only supplied in the second call 'after the person has approved the summary'. It does not add format details for the answers values themselves.

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 and resource ('Submits an enquiry to Cyprus Non-Dom Calculator') and immediately disambiguates it from what an agent might assume ('NOT a purchase, NOT a guaranteed quote'). Combined with the title's mention of human providers, an agent can distinguish this from calculate, enquiry_fields and enquiry_describe without opening any 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 gives explicit when-to-use instructions for two distinct invocation modes: Step 1 'call with the answers ... and consent=true', Step 2 'only if the person agrees, call again with the same answers, consent=true and the confirmation token'. It also names the sibling tool (enquiry_fields) as the source of field keys and states the pre-condition for step 2 (person approval), leaving nothing to inference.

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