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

With no annotations, the description carries more burden, but it does disclose the key behavioral trait that missing inputs fall back to documented defaults. It also enumerates the outputs, which is useful given there is no output schema. However, it does not describe whether the calculation is pure/read-only, what the output format looks like, or any constraints beyond what the schema already states.

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-loads the action plus output list, but the opening repeats 'EU drivers' hours calculator: driving time and rest periods calculator' redundantly. The final sentence about defaults is useful, but the overall phrasing could be tighter.

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 five optional parameters with full schema descriptions and no output schema, the description is nearly complete: it names the outputs and notes default fallback behavior. It stops short of describing the return structure or calculation caveats, but an agent has enough information 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 explains each parameter and its default. The description adds only the general statement that missing inputs use documented defaults, which is consistent with but not richer than the schema. Baseline 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 identifies the tool as an EU drivers' hours calculator and lists the specific outputs it produces: remaining driving today, time before a 45-minute break, weekly and fortnightly remaining driving. This is clear enough to distinguish it from the unrelated sibling tools, though the opening phrase redundantly restates the title.

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 by 'Run the EU drivers' hours calculator' and the enumerated outputs, but there is no explicit guidance about when to use this tool versus alternatives or when not to use it. Since the sibling tools are not similar calculators, the lack of alternative routing is less harmful, but the description still provides only implied usage 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?

No annotations are provided, so the description carries the burden. It does disclose the content categories returned (inputs with units/ranges/defaults, outputs, assumptions, tables), which is useful, but says nothing about format, size, or that the tool performs no computation and has no side effects.

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 compact sentence that front-loads the content categories. It is a noun phrase without an explicit verb, which slightly weakens readability, but nothing is padded.

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?

With no output schema and no parameters, the description does a fair job enumerating what is returned. It stops short of telling the agent what to do with the result - e.g., that the returned spec should drive a subsequent `calculate` call - leaving the workflow incomplete.

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 zero parameters, so the baseline is 4. The description's mention of input units, ranges, and defaults refers to the described calculator, not to this tool's own arguments, which is not misleading 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 description names a specific resource - the inputs, outputs, assumptions, and tables of the EU drivers' hours calculator - which is a precise scope. It is clearly the documentation counterpart to the `calculate` sibling, though it never states that relationship explicitly, so differentiation is left to inference.

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 statement of when to call this versus `calculate` or `enquiry_describe`. The agent must guess that this is a pre-flight discovery call rather than a computation, and no conditions or prerequisites are given.

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 disclosure burden and does it well: it states that nothing is bought, ordered or paid, no quote is guaranteed, and it is free. It also discloses the content of the return (recipients, consent wording, confirmation), although it does not explicitly mark the tool as read-only.

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 brief and front-loads the most important instruction ('Read first') and the core clarification about what submission really means. The sentences are compact, though the 'Also returns' clause is a bit compressed.

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 no output schema and no parameters, the description covers the essential context an agent needs: the nature of the enquiry, the absence of payment/quote guarantees, and the content returned. It could add an explicit statement about the tool's own output, but it is largely complete for a zero-parameter explainer.

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 adds useful semantic context about what the submission entails and what information is returned, compensating fully for 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 description names a specific verb ('states plainly'), a resource ('what submit_enquiry does on HGV Hours Calculator'), and distinguishes it from the actual submission tool by clarifying that no purchase or quote is involved. It clearly positions enquiry_describe as the explanatory companion to submit_enquiry among the sibling 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?

'Read first' explicitly tells the agent when to invoke this tool, before using submit_enquiry. It does not spell out exclusions relative to calculator_describe or enquiry_fields, but the positioning is clear enough for routing.

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 disclosure burden. It transparently states the content scope and the conditional 'where there are any' for options, but says nothing about return structure, whether the field list is static or dynamic, or other operational behavior. 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?

Two sentences, front-loaded with the content scope and closed with a practical usage pointer. Every sentence earns its place 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, no-output-schema metadata tool, the description covers what it returns, the fields included, and how to use the result downstream. The only small gap is not specifying the response format, and the boundary with enquiry_describe remains implicit rather than explicit.

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 zero parameters and the schema is empty, so there is no parameter semantic gap for the description to fill, meriting the baseline 4. The mention of field keys is relevant to submit_enquiry's parameters, not this tool's 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 resource (HGV Hours Calculator enquiry fields) and enumerates the exact content returned (key, label, type, required, help text, options). It lacks an explicit verb like 'lists' or 'returns', and its boundary against the similar sibling enquiry_describe/calculator_describe is only implied, so it doesn't reach a 5.

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 second sentence gives actionable guidance: answers passed to submit_enquiry must be keyed by the field keys from this tool. This clearly establishes when the tool is needed, though it doesn't explicitly state when not to use it or name alternatives.

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 exist, so the description carries the full burden and does so: it discloses that step 1 validates and returns a summary/consent line/token, that step 2 triggers an email with a click-to-confirm link required before any provider sees the data, and that details go to up to three chosen specialists with stop rights. These are exactly the behavioral facts an agent needs.

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?

Front-loads the critical 'NOT a purchase' caveat and structures the flow as Step 1/Step 2. The full consent text is embedded and largely duplicates the consent parameter description in the schema, which is the one place the wording could be trimmed.

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?

With no output schema, the description compensates by explaining what each call returns (summary, consent line, confirmation token) and the downstream email/confirmation consequence. For a two-phase nested-object tool 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 is 3, but the description adds sequencing meaning: answers are keyed by field key from enquiry_fields, consent=true is a hard requirement with defined semantics, and confirmation is only supplied on the second call. That sequencing context is not derivable from the schema alone.

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?

States a specific verb (submits), resource (an enquiry), and scope ('NOT a purchase, NOT a guaranteed quote'), and outlines the two-step flow. An agent can distinguish this from the calculate/calculator_describe/enquiry_* siblings without opening a 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?

Gives explicit call conditions: Step 1 with answers+consent=true, then Step 2 'only if the person agrees' with the same answers plus the confirmation token. The gating condition for the second call is stated, not left to inference.

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