site

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It does disclose what the calculator returns and mentions default fallback behavior, but it does not explicitly state that this is a read-only computation or explain any state-law assumptions or limitations.

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, and each sentence earns its place: the output list is valuable and the defaults note is useful. The redundant phrase "calculator calculator" is a minor quality flaw that prevents a 5.

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?

Since there is no output schema, the description usefully enumerates the four result categories. Combined with fully described input parameters and default behavior, an agent can understand and invoke the tool correctly, though state-specific caveats are left implicit.

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 fully documents all four parameters and their defaults. The description adds only a generic statement about missing inputs falling back to defaults, which provides no meaningful semantic detail 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 clearly states the action ("Run the Long service leave calculator") and the resource, and it lists the four computed outputs, which makes the tool's purpose concrete. It does not explicitly name sibling tools, but the calculation-focused language distinguishes it from the describe/enquiry 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 no guidance about when to use this calculator versus alternatives like calculator_describe or enquiry_fields. The only usage-related information is that missing inputs fall back to defaults, which is helpful but not sufficient for routing an agent to this 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 provided, the description carries the burden of behavioral disclosure. It conveys that the tool returns descriptive metadata about the calculator rather than performing calculations, and it names the specific content areas. It does not explicitly state that the tool is read-only or side-effect free, though zero parameters and the 'describe' framing make that largely implicit.

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 sentence that efficiently enumerates the tool's content coverage: inputs with units/ranges/defaults, outputs, assumptions, and tables. There is no redundant phrasing or filler, and the structure is easy to parse.

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, descriptive tool with no output schema, the description adequately states what an agent will learn by calling it. It covers the main content categories but does not go into details such as format, length, or how the information is presented. Given the tool's simple purpose, this is nearly complete but slightly thin on delivery expectations.

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 schema description coverage is 100%, so the schema is trivially complete. The description adds context by noting that the calculator itself has inputs with units, ranges, and defaults, which is useful for agents inspecting the calculator. The baseline of 4 for zero-parameter tools 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 resource (the Long service leave calculator) and the scope of information it covers: inputs, outputs, assumptions, and tables. It is distinct from the sibling 'calculate' tool because it describes rather than executes, though it uses an elliptical noun-phrase rather than an explicit verb like 'returns' or 'describes'.

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 tool should be used when an agent needs to know the calculator's inputs, outputs, assumptions, or tables. However, it does not explicitly state when to use this tool versus 'calculate' or any other sibling, nor does it mention 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 must carry behavioral disclosure. It does describe the informational output ('returns who receives the details, the consent wording, and how the person confirms'), but it never explicitly states that calling this tool has no side effects or does not itself submit an enquiry. The bulk of the text describes submit_enquiry's behavior, creating mild ambiguity about the describe tool's own 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?

Two sentences with no filler: 'Read first' front-loads the usage warning, the middle sentence states the core purpose, and the final sentence summarizes the return value. Every clause 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 parameterless, annotation-less describe tool, the description covers what it does, what it returns, and when to read it. It is nearly complete, but an explicit 'this tool does not submit anything' would fully remove the potential confusion 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 input schema has zero properties, so there are no parameters to document; the 0-parameter baseline of 4 applies. The description adds no parameter information, 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 description identifies a specific verb ('States plainly') and resource ('what submit_enquiry does on Long Service Leave Calculator'), and makes the tool's informational role clear against siblings like submit_enquiry. The title and phrase 'Read first' reinforce that this is a pre-submission explainer, not the action itself.

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' is a direct usage cue: call this before acting on submit_enquiry. It names the tool it explains, giving clear context, though it does not explicitly list when-not-to-use alternatives such as calculator_describe or enquiry_fields.

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 transparency burden. It conveys that the tool exposes field metadata and how that metadata should feed into submit_enquiry, which implies a read-only metadata retrieval purpose. But it never explicitly states the operational behavior, such as whether it returns a list/object or 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?

The description is one focused sentence, front-loaded with the core purpose and followed by a practical usage pointer. There is 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?

For a zero-parameter metadata tool, the description covers the essential content and the follow-up action. It lacks an explicit statement about the return structure, but the enumerated field attributes give enough context for an agent to invoke and use the result.

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, so parameter-level semantics are not needed. The description correctly focuses on what the tool returns and how to use it, matching the 0-parameter baseline.

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 ('every field of the Long Service Leave Calculator enquiry') and the information exposed (key, label, type, required, help text, options). It is clear and specific, but it does not explicitly distinguish itself from the sibling enquiry_describe, so it stops short of 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 description provides actionable usage context by instructing the agent to pass answers to submit_enquiry keyed by field key. It does not, however, discuss when to prefer this tool over the similar-sounding enquiry_describe or calculator_describe, so exclusion guidance is missing.

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 validation behavior, the returned summary/consent line/token, that the enquiry is not visible to providers until the person clicks an emailed link, and that details go to up to three providers. This is unusually rich behavioral context for a mutation tool.

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 with purpose and the not-a-purchase caveat, then the two steps in order. The long embedded consent quotation is bulky but is the actual text the agent must present, so it earns its place; minor redundancy in repeating consent=true across both steps.

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 exists, and the description compensates by explaining what step 1 returns (summary, consent line, token) and what happens after step 2 (email with a link gating provider visibility). For a nested-answer, multi-step tool, this is complete enough to invoke 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 baseline is 3, but the description adds value by tying parameters to the flow: answers are keyed by field key from enquiry_fields, consent must be true in both steps, and confirmation is the token returned by step 1. It stops short of describing answer value types or required fields, which the schema covers.

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 (submits an enquiry to Long Service Leave Calculator) and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote', which separates it from calculate and the describe siblings. The two-step nature is made explicit up front.

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 sequencing: Step 1 call with answers and consent=true to validate; Step 2 only if the person agrees, call again with the confirmation token. It also names the prerequisite that consent must reflect the person having read and agreed to the quoted text. Nothing about when to invoke each step is left to inference.

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