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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 burden of behavioral disclosure. It does disclose one meaningful behavior: missing inputs fall back to documented defaults. However, it does not explicitly state that the tool is a pure calculation with no side effects, nor does it clarify the return format or whether the listed items are outputs.

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 concise and front-loaded with the tool's purpose, but the duplicated word in 'calculator calculator' is sloppy. The colon-separated list of output values is compact, but it is not clearly labeled as outputs or inputs, which slightly weakens the structural clarity.

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 calculator with three well-documented parameters, the description gives the core purpose and hints at the outputs. However, with no output schema and no annotations, it should more explicitly state what the tool returns and ideally the relationship between the inputs and listed output values. It also omits any connection to sibling tools.

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 provides 100% parameter coverage with descriptions and defaults for profit, refundType, and distributed. The description adds no additional parameter-level meaning, so the baseline score of 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 clearly identifies the tool as the Malta shareholder refund calculator and lists the key values it handles: Malta tax paid, profit available to distribute, dividend paid, and shareholder refund claimable. However, it does not explicitly distinguish itself from sibling tools like calculator_describe or enquiry_describe, and the repeated word 'calculator' creates minor ambiguity.

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 guidance about when to use this tool versus the sibling tools such as calculator_describe, enquiry_fields, or submit_enquiry. The only usage-related note is that missing inputs fall back to defaults, which addresses parameter handling rather than tool 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what content will be returned (inputs, outputs, assumptions, tables), but says nothing about side effects, authorization requirements, or the output format. For a read-only describe-style tool, this is adequate but not rich.

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 compact sentence that front-loads the three things an agent will learn: inputs with units/ranges/defaults, outputs, and assumptions/tables. There is no filler, and the title adds necessary context about the specific calculator.

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 documentation tool with no output schema, the description covers the essential scope well: it lists inputs, outputs, assumptions, and tables. It lacks an explicit pointer to the sibling 'calculate' tool or details about the returned format, but overall it is sufficiently complete for its simplicity.

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 parameters and 100% schema description coverage, so there are no parameter meanings for the description to add. The phrase 'inputs this calculator takes' refers to the underlying calculator's domain inputs rather than MCP tool parameters, which is mildly ambiguous but not harmful given the empty 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 title and description together clearly identify a documentation/reference tool for the Malta shareholder refund calculator. It names exactly what the tool covers: inputs, outputs, assumptions, and underlying tables. However, the description lacks an explicit verb such as 'describes' and does not contrast with the sibling 'calculate' tool.

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?

Usage is implied: an agent would call this when it needs to understand the calculator's inputs, outputs, or assumptions. The description does not explicitly state when to use this versus 'calculate', nor does it mention any prerequisites or exclusions.

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 usefully discloses that nothing is bought, ordered, or paid; no quote is guaranteed; the service is free; and it returns who receives the details, consent wording, and confirmation process. The only weakness is that the description shifts between describing submit_enquiry and describing this tool, slightly blurring whether these consequences apply to the call itself or to the enquiry being described.

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 with the 'Read first' instruction. Every sentence contributes something meaningful: scope, key caveats, and returned content. There is no filler or repetition.

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 informational tool with no output schema, the description adequately explains what the tool returns and sets user expectations about the enquiry process. It could be slightly more explicit that calling this describe tool itself does not submit an enquiry, but overall it is sufficient for an agent to select and 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 accepts zero parameters and the schema fully documents this with an empty properties object. There is nothing for the description to add about parameter meaning, so the baseline of 4 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 clearly states the tool's function: it explains what submit_enquiry does on the Malta Tax Refund Calculator. It distinguishes this from purchase or guaranteed-quote actions, and the title reinforces the scope. This makes it easy to tell apart from siblings like calculator_describe and submit_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?

The opening 'Read first' explicitly signals when to use this tool: before engaging with submit_enquiry. It does not explicitly contrast with alternatives like calculator_describe or enquiry_fields, but the context and purpose are clear enough for an agent to infer appropriate use.

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 this is a read-only metadata operation and describes the output contents. It does not explicitly state 'returns a list' or mention absence of side effects, but the intended behavior is unambiguous from the wording.

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: it immediately identifies the resource and enumerates the returned attributes in one dense sentence, followed by a single actionable instruction. Every sentence contributes meaningful information with no filler.

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 tool without an output schema, the description is nearly complete: it enumerates the field attributes and explains how to use them with submit_enquiry. A minor gap is that it does not explicitly describe the response container (e.g., list vs object), but this is unlikely to prevent 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?

The tool has zero parameters, so the description has no parameter semantics to explain. The baseline for zero-parameter tools is 4, and the description adds value by linking field keys to the submit_enquiry tool, which helps the agent understand how to use the returned data.

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 precisely states what the tool provides: every field of the Malta Tax Refund Calculator enquiry, including key, label, type, required flag, help text, and allowed options. This clearly differentiates it from siblings like calculate, submit_enquiry, and enquiry_describe by describing a metadata-retrieval resource.

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 gives actionable usage guidance by telling the agent to pass answers to submit_enquiry keyed by field key, making the integration point explicit. It does not explicitly enumerate alternatives or exclusions, but the context is clear enough for an agent to select this tool when field definitions are needed before submission.

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 full burden of behavioral disclosure, and it does so thoroughly. It reveals the validation step, the return of a summary and confirmation token, the requirement to send the confirmation token on the second call, the email with a click link, and that providers only see the enquiry after the person clicks. It also explicitly states this is not a purchase or guaranteed quote.

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 long but every sentence earns its place: it front-loads the critical 'not a purchase, not a guaranteed quote' distinction, then structures the two steps in order, and ends with the exact consent wording. The stepwise structure mirrors the actual invocation flow, making it easy for an agent to follow.

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 has a nested answers object, an optional confirmation parameter, no output schema, and the complexity of a two-step consent workflow, the description is complete. It explains what to expect from step 1 (summary, consent line, confirmation token), when to send the confirmation token, and what happens after submission, including the email link requirement. No critical missing context remains 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?

The schema already describes all three parameters with 100% coverage, so the baseline is 3. The description adds meaningful context beyond the schema by explaining that answers are keyed by field key from enquiry_fields, that consent has a specific exact text, and that confirmation is the token from step 1 after approval. This elevated guidance justifies a 4.

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 ('submits an enquiry'), identifies the resource (Malta Tax Refund Calculator human providers), and clearly differentiates from a purchase or guaranteed quote. It also explains the two-step nature, making the tool's role unambiguous relative to sibling calculator tools.

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 gives explicit step-by-step usage: call first with answers and consent=true, show the summary and consent line, then call again only if the person agrees, including the confirmation token. It also states the condition for consent and the required post-submission action, leaving no ambiguity about when and how to invoke the tool.

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