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

Since no annotations are provided, the description carries the disclosure burden. It does add useful behavior: missing inputs fall back to documented defaults. However, it does not state whether the tool is side-effect-free, whether it reads external data, or what happens on invalid input.

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, but it contains a duplicated phrase ('calculator calculator') and a slightly run-on colon list. It is concise in size but not polished in structure.

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?

The description lists several result areas and the default fallback behavior, which helps since there is no output schema. Still, it omits the return format and any guidance on how this tool relates to calculator_describe, leaving an agent to infer important context.

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 every parameter's meaning and default. The description only reiterates the default fallback behavior, adding no new parameter-level insight.

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 action ('Run') and resource ('New Zealand notice period calculator'), and it lists the calculation output areas. It does not explicitly distinguish itself from calculator_describe, but the verb and output list make it recognizable as the compute 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?

There is no guidance on when to use this tool versus calculator_describe or the enquiry siblings, and no stated exclusions or prerequisites. The only hint is the imperative 'Run', which is implicit rather than explicit.

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. It states that the tool exposes the assumptions and tables behind the calculator, which is useful transparency about what the returned description will contain. It does not explicitly declare 'read-only' or list side effects, but for a describe-style tool with zero parameters this is reasonably clear.

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 covers all core aspects of the tool: inputs, outputs, assumptions, and tables. It is front-loaded and contains no filler, while the title adds complementary context without 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 and no parameter schema, so the description must stand alone. It adequately enumerates the categories of information returned by the tool. It could be strengthened by explicitly mentioning the relationship to 'calculate,' but for a zero-parameter documentation tool, the description is largely complete.

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 already fully reflects that. The description adds meaningful context by noting that the calculator's own inputs are presented with units, ranges, and defaults, which helps an agent understand the kind of information the describe output will contain.

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 enumerates what the tool covers — the calculator's inputs with units/ranges/defaults, outputs, assumptions, and tables — and the title/name make it obvious this is a describe/reference tool rather than the calculation tool itself. It lacks an explicit standalone verb like 'returns,' but the scope is unmistakable and distinguishes it from the sibling 'calculate'.

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 is the documentation/reference tool for the New Zealand notice period calculator, but it never explicitly states when to use it instead of 'calculate' or whether it should be consulted before performing a calculation. No exclusions or alternatives are named, leaving the agent to infer usage from the sibling tool names.

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 well: it discloses that nothing is bought, ordered, or paid, that no quote is guaranteed, that the enquiry is free, and that the tool returns recipient details, consent wording, and confirmation behavior. 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?

The description is tight and front-loaded with the 'Read first' instruction, followed by a concise explanation of the tool's subject and return values. Every sentence contributes distinct, useful information with 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 parameterless informational tool with no output schema, the description is complete: it specifies the subject, the key caveats, and the three return elements. Nothing essential is missing for an agent to call and interpret the 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 input schema is empty, so the zero-parameter baseline of 4 applies. There are no parameters for the description to elaborate on, and it does not misleadingly imply any inputs.

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 an explainer: it 'states plainly what submit_enquiry does' and lists what it returns. It is distinct from siblings like submit_enquiry and calculate because it is explicitly descriptive rather than action-oriented.

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 phrase 'Read first' gives clear timing guidance: use this tool before the enquiry/submission workflow. It does not explicitly list alternatives or when-not-to-use conditions, but the intended context is strongly implied.

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 behavioral burden. It discloses that the tool is a complete field listing and positions it as a prerequisite for submit_enquiry rather than a submission endpoint. It does not explicitly mention output formatting or idempotence, but for a zero-parameter metadata getter these are minor.

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, no filler: the first defines the tool's content, the second tells the agent how to use the result. The key usage note comes immediately after the field list.

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?

The description is complete enough for a no-argument metadata tool: it names every data category returned and connects the result to submit_enquiry. It does not describe the exact return envelope, but the absence of an output schema is partially mitigated by the explicit field list.

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 description coverage, so the baseline is 4. The description adds no parameter detail, but none is needed.

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 resource (all fields of the Notice Period Calculator NZ enquiry) and enumerates the attributes returned (key, label, type, required, help text, allowed options). It is more specific than the title, though it lacks an explicit verb such as 'returns' or 'lists'.

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 states the actionable context: answers are passed to submit_enquiry keyed by the field key, which tells an agent why to call this tool. It does not explicitly compare against siblings like enquiry_describe or state when not to use it.

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 load and does so well: it discloses validation behavior, what step 1 returns (summary, consent line, confirmation token), that step 2 causes real submission, and that a double opt-in email link must be clicked before any provider sees the data. It also clarifies the consent semantics and the cap of three providers.

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-loaded and dense — the disambiguation comes first, then the numbered steps. It loses a little economy by reproducing the full consent paragraph verbatim from the schema's consent description, but that text is arguably needed so the agent can show it to the person.

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?

No output schema or annotations exist, yet the description covers the return payload of step 1, the effect of step 2, and the post-submission verification email. Nothing an agent needs to drive the correct sequence is missing.

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 genuine meaning beyond it: 'answers' is keyed by field key from enquiry_fields, 'consent' must be true at both steps, and 'confirmation' is the step-1 token that is only supplied on the approved second call. That is flow-level semantics the schema cannot express.

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 and resource (submit an enquiry to Notice Period Calculator NZ) and immediately disambiguates it from adjacent concepts: 'NOT a purchase, NOT a guaranteed quote.' The two-step framing plus the reference to enquiry_fields makes its position relative to the sibling tools unmistakable.

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, sequential when-to-use rules: Step 1 calls with answers and consent=true, then show the returned summary and consent line; Step 2 is called 'only if the person agrees' and requires the confirmation token. The gating condition is stated, not inferred.

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