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

No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses useful behavior: missing inputs fall back to defaults and the result is a low/high quote range for 2026. However, it does not clarify output format, currency, or whether there are side effects beyond pure calculation.

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 second sentence about fallback defaults is useful and earns its place. However, the opening phrase 'Scaffolding cost calculator calculator' is redundant and the title already states the same information, so the structure 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?

For a relatively simple calculator with four well-documented parameters, the description gives the core purpose and the fallback behavior. But with no output schema and no annotations, it does not explicitly state what the returned low/high values look like or how to interpret them, leaving a notable gap.

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% and all four parameters already have meaningful descriptions and defaults in the schema. The description adds only the fallback-to-defaults behavior, which the schema's default values already imply, so the baseline of 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 clear verb ('Run') and resource ('Scaffolding cost calculator'), and adds that it produces low/high ends of typical 2026 quotes. It does not explicitly distinguish itself from sibling tools such as calculator_describe, so it falls 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?

There is no guidance on when to use this tool versus calculator_describe, enquiry_describe, or submit_enquiry. The description implies 'use this to calculate scaffolding costs' but does not state alternatives, exclusions, or prerequisites.

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 discloses the content domains covered (inputs, outputs, assumptions, tables), which is meaningful. However, it does not state whether the output is static text, structured data, or how long the result is, though for an informational tool this is largely acceptable.

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, efficient sentence that front-loads the core purpose and then enumerates the covered aspects without repetition or filler. Every clause adds distinct 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 zero-parameter, no-output-schema describe tool, the description adequately covers what an agent needs: the exact scope of content the tool will return. It does not specify the output format, but the boundaries of the tool are clearly defined.

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 there is nothing to document. The 0-params baseline is 4, and the description even adds value by noting the calculator's own inputs will include units, ranges, and defaults.

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 and resource: it describes the calculator's inputs (with units, ranges, defaults), outputs, assumptions, and tables. The title anchors it to the Scaffolding cost calculator, making it clearly distinct from siblings like calculate and 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?

There is no guidance on when to use this tool versus alternatives such as calculate, enquiry_describe, or enquiry_fields. Usage is only implied: when one needs the calculator's input/output details. No exclusions or alternative routing is provided.

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, and it succeeds. It explicitly states what does NOT happen (nothing bought, ordered, or paid; no quote guaranteed; free), what it returns (recipient, consent wording, confirmation method), and the overall behavior of starting an enquiry with human 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?

The description is tightly written and every sentence adds value: a directive, the core action, the key exclusions, and the return information. The important safety-oriented framing ('nothing is bought... no quote guaranteed... free') is front-loaded.

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 descriptive tool, the description fully covers what the agent needs: what the tool does, what it does not do, and what it returns. No essential information 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?

This tool has zero parameters, so there is nothing for the description to add beyond the empty input schema. The baseline of 4 applies, and no meaningful parameter semantics are 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 states plainly that this tool explains what submit_enquiry does, using a specific verb ('states') and a clear resource ('submit_enquiry' on Scaffolding Cost Calculator). It also differentiates itself from the actual submission tool by emphasizing this is information, not a purchase or guaranteed quote.

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' gives explicit positioning as a precursor to submit_enquiry, and the description makes clear this tool is informational rather than the action tool. It does not enumerate all sibling alternatives or when not to use it, but the context is clear enough for an agent to select it appropriately.

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 full burden. It implies a read operation by listing field attributes, but it does not explicitly state that the tool is read-only or has no side effects. It adds context about the data structure, but safety is not explicitly disclosed.

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 fluff. The first sentence front-loads the key information about the fields, and the second provides a practical usage hint. Every word 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 read tool, the description is complete: it specifies exactly what fields are returned and how to use the keys. It does not mention the exact response format (e.g., array vs object), but the phrasing 'Every field' implies a collection. Overall, sufficient 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 0 parameters, so the baseline is 4. The description does not need to explain parameters, and it correctly focuses on the output content. The schema coverage is 100% (vacuously), so no parameter information 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 states the tool's purpose: it lists every field of the enquiry (key, label, type, required, help text, options). The verb is implied but the resource is specific, and it distinguishes itself from submit_enquiry by mentioning how to use the returned keys.

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 explicit usage context: after retrieving fields, pass answers to submit_enquiry keyed by field key. This tells the agent when to use this tool (to get field metadata before submission). It does not mention alternatives like enquiry_describe, but the workflow is clear.

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 behavioral burden and does so: it discloses validation-on-first-call, the returned summary/consent line/token, the requirement that the person click an email link before any provider sees the enquiry, and the exact legal meaning of consent. These are non-obvious side effects an agent must know before invoking.

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 most important disambiguation ('NOT a purchase') and is organized as Step 1 / Step 2, so it reads cleanly. It is long and repeats the consent text verbatim from the schema, which is defensible (the agent must display it) but costs a little density.

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 the description compensates by describing what each step returns (summary, consent line, confirmation token) and what the end user receives (an email link with a click-to-confirm gate). For a nested-object, consent-sensitive, two-call flow, an agent has everything needed both to call it and to sequence 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 coverage is 100%, so the baseline is 3, but the description adds real meaning: answers are keyed by field key from the enquiry_fields sibling, consent must be set only after the person has read the quoted text, and confirmation is the token returned by step 1 rather than any arbitrary string. That exceeds the schema's own wording.

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 Scaffolding Cost Calculator') and immediately fences off the adjacent-but-different actions ('NOT a purchase, NOT a guaranteed quote'). Combined with the title's 'two steps', an agent can distinguish this from calculate/enquiry_fields without opening the 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 an explicit two-step protocol: Step 1 with answers + consent=true, then Step 2 only after the person approves, with the same answers plus the confirmation token. It also names the precondition for consent and the gating condition ('only if the person agrees'), 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.