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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 discloses the key behavioral trait that missing inputs fall back to documented defaults, and enumerates what the calculator evaluates for each scenario. Since this is a read-only calculation tool, there are no destructive side effects or auth requirements to disclose, and the description covers the meaningful computation 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 reasonably short and front-loads the purpose, but it contains redundancy: 'Run the IHT calculator: today vs April 2027 calculator:' repeats 'calculator' in a clunky way. The output list is useful, but the phrasing could be tightened without losing 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?

Given that there is no output schema and no annotations, the description does a good job of stating what the calculator computes and how defaults behave. It does not describe the return format or units, but for a calculator with all optional parameters and clear computation scenarios, the description is largely sufficient 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?

Schema description coverage is 100%, so the schema already documents all seven parameters in detail. The description adds no parameter-specific meaning beyond mentioning that missing inputs use defaults, which is already reflected in the schema defaults. Baseline 3 applies because the schema does the heavy lifting.

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 runs an IHT calculator comparing today's rules with April 2027 rules, and lists the exact computed outputs: estate today, estate from April 2027, tax-free allowance, and IHT under current rules. This is a specific verb with a specific resource and is not a tautology of the name or title. It also distinguishes itself from sibling calculator_describe by saying 'Run' rather than describe.

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: the tool is for calculating IHT under current and future 2027 rules, so an agent can infer when to invoke it. However, it does not explicitly state when not to use it or mention alternatives such as calculator_describe, so it falls just short of full routing guidance.

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 of behavioral disclosure. It does convey what the tool returns: documented inputs, outputs, assumptions, and tables. However, it does not explicitly state that the tool is read-only, does not perform calculations itself, or have any other behavioral characteristics, so the disclosure is only partially complete.

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 key content areas and adds useful parenthetical detail without any filler. Every phrase contributes to the agent's understanding of what the tool provides.

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, the description covers the essential content categories: input semantics, output semantics, and underlying assumptions/tables. It lacks an explicit statement about alternatives or the absence of side effects, but it is complete enough for an agent to decide to call it.

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 baseline is 4. The description does not introduce any confusion about tool arguments, and the mention of units, ranges, and defaults refers to the calculator's inputs that are described by this tool rather than to the tool's own parameters.

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 resource (the IHT calculator) and specifies what the tool will convey: inputs with units/ranges/defaults, outputs, assumptions, and tables. However, it is a noun phrase rather than an explicit verb statement like 'Returns...' or 'Describes...', and it does not explicitly differentiate from sibling describe tools such as enquiry_describe.

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 guidance is given about when to use this tool versus alternatives like calculate or enquiry_describe. The description implies that this is the tool for understanding the calculator's behavior, but it never states conditions, exclusions, or which sibling to use instead.

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 and does so excellently. It discloses that nothing is bought, ordered, or paid, that no quote is guaranteed, that it is free, and it previews the returned content: recipients of details, consent wording, and confirmation method.

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?

Three short sentences with zero filler. The critical directive 'Read first' is front-loaded, followed by the core behavior and then the return-value highlights. Every sentence 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?

For a zero-parameter explanatory tool with no output schema, this is complete. It states the purpose, scope, what is NOT true about the action, cost, and exactly what information the user will receive. An agent has everything needed to invoke and interpret this 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?

The tool has zero parameters, so parameter explanations are unnecessary; the baseline of 4 applies. The description adds useful context about what the tool returns instead of parameter details, which is appropriate here.

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 verb 'states plainly' plus the specific resource 'what submit_enquiry does on IHT 2027 Calculator' makes the purpose unmistakable. The title further differentiates it from a purchase or quote, so an agent can tell this is explanatory rather than transactional.

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' gives a clear cue to consult this tool before acting, and the description explicitly frames it as the preface to submit_enquiry. It does not name sibling tools like calculator_describe as alternatives, but the context is strong 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 must carry the burden of behavioral disclosure. It reveals the returned content well but does not explicitly state that this is a read-only retrieval, whether any authentication is needed, or how the result is structured. This is a minor gap for a simple metadata-listing tool, but still a 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 compact, front-loaded with the resource identity, and every clause adds value: the field list is specific and the downstream usage hint is actionable. 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?

There is no output schema, so the description correctly compensates by enumerating the returned field attributes. It provides enough context for an agent to know what the tool returns and how to use the field keys. It could give a small example or clarify the 'type' values, but overall it is adequately complete for a low-complexity metadata 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?

There are zero parameters, so the schema adds nothing and the baseline is 4. The description adds useful semantics by explaining what the returned fields represent and how the field keys should be used with submit_enquiry.

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 resource ('every field of the IHT 2027 Calculator enquiry') and the specific attributes it exposes (key, label, type, required, help text, allowed options). Although there is no explicit verb like 'returns' or 'lists', the meaning is unmistakable and it is clearly distinguished from the sibling submit_enquiry and enquiry_describe 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 tells the agent that answers should be passed to submit_enquiry keyed by these field keys, which establishes the main use case. It does not explicitly name alternative tools for different scenarios, but the context is sufficient to understand when this tool is needed.

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 so: it discloses the write/consent boundary, the double opt-in (the person must click an emailed link before any provider sees the enquiry), that details go to up to three firms chosen by the calculator, and that the person can stop further firms receiving details. It also names the three return artifacts of step 1 (summary, consent line, confirmation token).

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 key disambiguation ('NOT a purchase') is front-loaded and the two steps are ordered and labelled. The full consent text is quoted verbatim and partly duplicates the schema's consent description, which is justified only because the agent must show that exact line to the person, but it does add length.

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, yet the description explains what step 1 returns and what happens after step 2, so the agent knows the full lifecycle before and after the call. For a two-phase, consent-gated submission tool with a nested object parameter, the coverage of flow, prerequisites and outcome is sufficient 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: 'answers' is keyed by field key from the enquiry_fields sibling, 'consent' must be true only after the person has agreed, and 'confirmation' is the token produced by step 1 after approval. Only the shape of the answers values is left to 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 (submits) and resource (an enquiry to human providers), and immediately draws the boundary that matters most: 'NOT a purchase, NOT a guaranteed quote.' It is clearly distinguishable from calculate, calculator_describe, enquiry_describe and enquiry_fields.

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 spells out an explicit two-step protocol: step 1 is called with answers plus consent=true to validate, step 2 is called 'only if the person agrees' with the same answers plus the confirmation token. The preconditions for each call and the human-approval gate between them leave nothing to inference.

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