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

No annotations are provided, so the description must carry behavioral information. It usefully discloses that missing inputs fall back to documented defaults and indicates that cost figures are computed. However, it does not state whether the operation is read-only, whether any state changes occur, or what the returned result structure is.

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 front-loads the action and then lists the relevant calculated metrics without padding. The semicolon list is a little ambiguous about whether items are inputs or outputs, but overall the description is economical and appropriately sized.

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 nine-input tool with no output schema and no annotations, the description supplies only a terse list of possible outputs and the default-fallback behavior. It does not explain the ownership-crossover result, the output format, or how inputs map to outputs, leaving some interpretation gaps even though the schema fully documents the parameters.

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 full coverage with descriptions and defaults for all nine parameters, so the description does not need to re-explain them. The description adds high-level context about outputs but no parameter-specific semantics, formulas, or mappings beyond what the schema already provides.

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 a specific resource (the Charter cost and ownership crossover calculator), and it lists the figures the calculator produces. It is clearly distinct from calculator_describe, though it does not explicitly contrast itself with any sibling.

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 intended use is implied: this tool executes the calculator, while calculator_describe likely describes it. However, there is no explicit when-to-use or when-not-to-use guidance, no stated alternatives, and no mention of conditions that would make a sibling tool more appropriate.

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 burden of explaining behavior. It conveys that the tool is informational and returns details about the calculator, but it does not explicitly state that it performs no calculation, has no side effects, or describe the response format.

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 core content. It is efficient, though slightly awkward as a sentence fragment without a main verb.

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-style tool with no output schema, the description adequately lists what the tool will explain: inputs, outputs, assumptions, and tables. It could be more explicit about what the tool itself returns, but the purpose is clear enough for 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 input schema has zero parameters, so the baseline is 4. The description appropriately focuses on the calculator's inputs rather than the tool's own parameters, so no parameter documentation is missing.

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 indicates the tool provides information about a calculator: its inputs, outputs, assumptions, and tables. This distinguishes it from a calculation tool, though it does not explicitly contrast it with siblings like 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?

The intended use is implied: an agent would call this to understand the calculator before using calculate. However, there is no explicit statement about when to prefer this over alternatives or 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 burden and discloses both the nature of the tool (it states/returns information, not a purchase) and the specific return content: who receives details, consent wording, and confirmation method. It stops short of explicitly saying this tool itself makes no changes, but the 'Read first' and 'States plainly' phrasing make that clear enough.

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 four purposeful sentences with no filler: a directive, the core function, the key disclaimers, and the return contents. It is front-loaded with 'Read first' and 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 informational tool with no output schema, the description fully covers what the agent needs: what the tool explains, the key caveats (free, no guarantee, no purchase), and what it returns. Nothing critical is missing 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 input schema has zero parameters, so there is nothing for the description to explain. Baseline 4 applies; no parameter documentation gap exists.

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 uses a specific verb ('States plainly') with a specific subject ('what submit_enquiry does'), and the title reinforces the scope. It clearly positions the tool as a descriptive precursor to submit_enquiry, distinguishing it from the actual action tool and sibling 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?

'Read first' is an explicit directive to invoke this before the action tool, and the description frames it as the explanation of submit_enquiry's behavior on Charter vs Own. It does not explicitly name when not to use alternatives like enquiry_fields, but the context is clear enough for an agent to recognize this as the informational first step.

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, and it covers the key behavior: the returned field metadata includes requiredness and conditional options. It does not explicitly state that the tool is read-only or describe errors, but the read-only nature is strongly implied by describing a field dictionary rather than a mutation.

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. The first sentence enumerates exactly what the field metadata includes, and the second sentence connects the output to the submission flow.

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?

Despite having no output schema, the description fully specifies what the tool returns and how that return value should be used. For a zero-parameter metadata getter, nothing material is missing for an agent to call 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 has zero parameters, so the schema is trivially complete and there is no parameter burden. The description adds useful guidance by explaining that the returned field keys are the same keys used when submitting answers.

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 precisely what the tool exposes: every field of the Charter vs Own enquiry with key, label, type, required flag, help text, and options. This clearly distinguishes it from submit_enquiry, which receives answers rather than returning field metadata.

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 gives a clear usage context: obtain the field dictionary first, then pass answers to submit_enquiry keyed by field key. It does not explicitly enumerate when not to use it or alternative tools, but the linkage to submit_enquiry makes the intended workflow unambiguous.

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 well: it explains the two-step token flow, the double opt-in email link before providers see anything, and the exact consent scope. It doesn't mention error handling, validation failure modes, or rate limits, which would push it higher.

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 step-by-step structure is logical and front-loaded with the most important caveat (not a purchase). It's longer than ideal because the full consent sentence is repeated almost verbatim from the schema, which is redundant, but the flow remains clear.

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 nested, multi-step, stateful submission tool with no output schema and no annotations, the description covers the full lifecycle: call, show summary, confirm, token, email verification. An agent has everything needed to invoke both steps 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 three parameters, including the full consent text and the confirmation token's role. The description reinforces the step sequencing but adds little parameter detail beyond what the schema provides, so 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 states a specific verb+resource ('Submits an enquiry to Charter vs Own') and immediately disambiguates it from related operations with 'NOT a purchase, NOT a guaranteed quote'. Combined with the title, an agent can tell exactly what this tool does and differentiate it from the calculate/describe siblings.

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 gives explicit when-and-how guidance: Step 1 with answers and consent=true, then Step 2 only after the person approves the summary. It even describes the user-facing interaction flow (show the summary and consent line), leaving nothing to inference.

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