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

With no annotations, the description carries the burden of behavioral disclosure. It does add one useful behavioral trait: missing inputs fall back to documented defaults. However, it does not disclose whether the calculation is purely read-only, whether it performs any external data lookups, or how the output is returned. For a simple calculator the default-fallback note is helpful, but more behavioral context would be expected.

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 key outputs, making it easy to scan. The 'calculator calculator' phrasing is redundant, and 'documented defaults' is slightly indirect, but overall every element contributes useful 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?

For a four-parameter tool with no output schema, the description lists what will be calculated and mentions default fallback behavior, but it does not explain the output format or detail how each input affects the results. It is functionally adequate but leaves the agent to infer some details, especially because the tool has no annotations and no output schema.

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 four parameters and their defaults. The description adds only marginal semantic value by referencing EBITDA and the multiple, but it does not clarify cash/debt roles beyond what the schema provides. Baseline 3 is appropriate 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 says to run a business valuation calculator and enumerates the outputs (enterprise value, indicative value to shareholders, median multiples), so an agent understands what the tool does. It also distinguishes itself from sibling describe/enquiry tools by using the imperative 'Run'. The redundant 'calculator calculator' wording and lack of explicit sibling differentiation keep it from 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?

No explicit guidance is given about when to use this tool versus siblings like calculator_describe or submit_enquiry. The description implies this is the computational tool among the siblings, but it never states intended scenarios, exclusions, or prerequisites. An agent must infer usage context from the tool name and sibling 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 provided, the description carries the full burden. It accurately conveys that the tool returns explanatory information about inputs, outputs, and assumptions, implying a read-only informational behavior. However, it does not explicitly state that no calculation is performed or that there are 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 a single, well-structured sentence that front-loads the core purpose and enumerates the three key categories of information provided. Every word earns its place, and there is no wasted or redundant content.

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 simple descriptive tool with no parameters and no output schema, the description adequately conveys what the agent will receive: inputs, outputs, and assumptions. It could be more explicit about return format, but given the low complexity, the explanation is sufficiently 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 has zero parameters, so the schema provides no meaningful parameter documentation. Per calibration, zero parameters warrant a baseline of 4; the description adds useful context by noting that the calculator's inputs include units, ranges, and defaults, which is relevant even though this tool itself takes no 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 states that the tool explains the calculator's inputs, outputs, and underlying assumptions, which is a specific resource and purpose. It distinguishes itself from sibling tools like calculate by focusing on description rather than computation, though it does not explicitly name alternatives.

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 the tool should be used to understand the calculator before using it, but it does not explicitly state when to use this versus the calculate sibling or any other alternative. There is no exclusion guidance or when-not-to-use information.

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 and no output schema, the description carries the full burden and handles it well. It discloses that nothing is bought, ordered, paid for, or guaranteed, that it is free, and it enumerates what the tool returns: recipient details, consent wording, and confirmation behavior. This is exceptional behavioral disclosure for an explanatory 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?

The description is compact and front-loaded: the imperative 'Read first' sets priority immediately, followed by a clear statement of purpose and consequences. Every sentence adds distinct value 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?

For a no-parameter, no-output-schema documentation tool, this description is unusually complete. It explains the purpose, the user-facing outcome, the non-transactional nature, and the return content. Nothing necessary for an agent to decide whether and when to call it 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?

The tool has zero parameters and an empty input schema, so the baseline is 4 because there is no parameter ambiguity. The description does not need to explain parameters, and it does not waste space attempting to.

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 plainly states what the tool does: it explains what submit_enquiry does on Business Worth Calculator. It also clarifies the outcome in user terms — an enquiry with human providers, not a purchase, order, or guaranteed quote — which strongly distinguishes it from the sibling tools. The title reinforces the non-transactional purpose.

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 explicit positional guidance to use this tool before submit_enquiry, and the description makes clear it is the explanatory companion to submit_enquiry. It does not explicitly name when-not-to-use it versus calculate or enquiry_fields, but the context and zero-parameter nature make the intended use apparent.

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 disclosure burden. It makes clear this is a read-only metadata enumeration — it returns field definitions and delegates submission to submit_enquiry — which is the key behavioral trait an agent needs. It does not describe the response format, but the side-effect risk of a zero-input introspection tool is inherently low.

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 tightly packed sentences with zero waste: the first lists the complete content scope, the second explains the downstream usage contract. The purpose is front-loaded and every phrase 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 tool with no inputs, no output schema, and simple introspection semantics, the description is nearly complete: it enumerates the full set of returned attributes and tells the agent how to connect them to the submission sibling. The only notable gap is an explicit statement of when to prefer this over the similarly named enquiry_describe.

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 schema coverage is 100%, so the framework baseline of 4 applies. There is no parameter burden to compensate for; the description even adds value by explaining that the returned field keys are the exact keys to use when calling 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 names a precise resource — 'Every field of the Business Worth Calculator enquiry' — and enumerates the exact content returned (key, label, type, required, help text, allowed options), which adds real specificity beyond the name and title. The verb is only implied ('returns/lists'), and sibling differentiation is implicit via the submit_enquiry reference rather than explicit.

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 instruction 'Pass answers to submit_enquiry keyed by field key' provides concrete guidance on how to consume the result, positioning this tool as the prerequisite for building a submission. However, it never explicitly contrasts with the sibling describe tools (calculator_describe, enquiry_describe), so an agent must infer when to choose this one over them.

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 behavioral burden and does so thoroughly. It discloses the two-step validation flow, the consent requirement with exact wording, the email notification, and the mandatory link click before providers see the enquiry. This is exceptional transparency.

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 long but every sentence is necessary for a two-step consent-gated submission tool. It is front-loaded with the core purpose and non-purchase warning, then logically walks through step 1 and step 2. No redundant fluff.

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 the tool's complexity, lack of annotations, and lack of output schema, the description is remarkably complete. It covers both calls, the confirmation token, consent text, what to show the user, and post-submission email behavior. An agent has enough information to use 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?

Although schema coverage is 100%, the description adds significant meaning beyond the schema. It explains that answers are keyed by field keys from enquiry_fields, that consent requires the exact agreement text, and that confirmation is the token returned from step 1. This workflow-level explanation makes parameter semantics much clearer.

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 action and resource: 'Submits an enquiry to Business Worth Calculator'. It clearly distinguishes the tool from a purchase or guaranteed quote, and the title emphasizes the two-step nature. This makes it immediately distinct from siblings like calculate or 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 description gives clear step-by-step usage instructions: first call to validate and get a confirmation token, then a second call only if the person agrees. It also states when not to use it ('NOT a purchase, NOT a guaranteed quote'). However, it does not explicitly name alternative sibling tools for other purposes, so it stops short of full exclusion guidance.

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