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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 full behavioral disclosure burden. It only restates the default-value behavior already visible in the schema and gives no indication of side effects, output format, assumptions, or validation. This is a thin behavioral description for a tool with no annotation safety context.

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 short but sloppy: 'calculator calculator' is a redundant typo, and the fragment after the colon is grammatically ambiguous. It is not well-structured enough to be considered cleanly concise.

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, so the description should clarify what the tool returns. It only offers a vague list with units for two items, and not whether the result includes costs, payback, or system specifications. For a tool with six inputs and no annotations, this is incomplete.

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 baseline is 3 even without parameter details in the description. The description adds no input-level meaning; the colon-list appears to describe outputs rather than inputs and does not clarify how 'bill', 'rate', 'orient', or 'battCost' map to the calculation.

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 repeats the title nearly verbatim with the redundant phrase 'calculator calculator', and the colon-list reads as outputs rather than an explicit purpose statement. It is unclear whether the tool computes costs, system design details, or both, and it does not differentiate itself from the sibling 'calculator_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 'calculate' versus 'calculator_describe', 'enquiry_describe', or 'submit_enquiry'. The only usage-related note is about missing inputs falling back to defaults, which is not enough to help an agent choose this tool over alternatives.

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 must carry the safety/behavior burden. It frames the tool as informational and lists the material it returns, but it never explicitly states that invoking the tool is a read-only operation and does not perform a calculation. The wording 'outputs it returns' could momentarily be read as the calculator executing.

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 sentence that front-loads the core content and packs useful specifics (units, ranges, defaults, outputs, assumptions, tables) with 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, no-output-schema description tool, the description fully covers what an agent will get: input specifications, return values, and the calculator's model assumptions. Nothing needed to call it correctly 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 input schema has zero properties, so there are no parameters to document; this meets the 0-params baseline. 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?

States exactly what the tool provides: the calculator's inputs with units/ranges/defaults, outputs, and underlying assumptions/tables. This clearly identifies the Florida solar cost calculator as the resource and distinguishes describe from calculate/enquiry 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?

The description implies the tool is for inspecting calculator metadata, but it never explicitly says when to use it instead of calculate or enquiry tools, and it gives no exclusion criteria. An agent could infer 'use when you need the calculator's assumptions and definitions,' but that guidance is not stated.

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?

There are no annotations, so the description must carry the burden. It discloses that the tool returns information (who receives details, consent wording, confirmation method) and describes the nature of submit_enquiry (free, no purchase, no guaranteed quote). However, it does not explicitly state that this tool itself is read-only or has no side effects, which is a minor gap for a meta-description 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 concise, with a clear directive ('Read first') front-loaded, followed by a straightforward explanation of what submit_enquiry does and what this tool returns. It avoids unnecessary elaboration and uses a logical 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?

For a description tool with no output schema, the description adequately covers what the agent will receive: who receives the details, the consent wording, and how confirmation occurs. It does not specify the exact output format (e.g., plain text or structured), but for an informational tool this is acceptable. It is complete enough for an agent to know what to expect.

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 baseline is 4. The description correctly omits parameter details since none exist, and it focuses on the output content instead. This is appropriate and adds no redundancy.

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 this tool explains what submit_enquiry does on the Florida Solar Cost Calculator. It uses a specific verb ('states plainly') and names the resource (submit_enquiry), distinguishing it from calculator_describe by context. The title also reinforces the non-purchase, non-guaranteed nature, which is helpful.

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 begins with 'Read first,' which implicitly instructs the agent to consult this tool before acting on submit_enquiry. However, it does not explicitly mention when to use this tool versus other siblings, nor does it state when not to use it. The guidance is minimal and relies on inference.

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 disclosing behavior, and it does so by specifying exactly what the tool returns: per-field metadata including allowed options. It conveys that this is a read-only lookup without stating side effects, and for a no-parameter introspection tool this is adequate.

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 short, information-dense sentences. The first states the payload contents; the second gives actionable downstream guidance. No filler or repetition.

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 tool, the description fully covers what the agent needs: the field metadata contents and how to pass answers to the submission tool. Nothing essential 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, which is fully captured by the empty input schema. The description does not need to explain parameters; it instead explains the output shape and how to use it with submit_enquiry, which is the more relevant semantic information.

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?

Clearly identifies the tool as returning the field schema of the Florida Solar Cost Calculator enquiry, enumerating key, label, type, requiredness, help text, and allowed options. It is unambiguously distinct from siblings like calculate, enquiry_describe, and submit_enquiry.

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?

Provides practical guidance for using the tool: 'Pass answers to submit_enquiry keyed by field key.' This tells an agent why to fetch these fields and how to use them downstream. It does not explicitly state when not to use it, but the intended 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?

With no annotations provided, the description carries the full burden, and it does so exceptionally. It discloses that the first call does not submit, what it returns (summary, consent line, token), the need for user approval, the second-call requirement, and the email link that must be clicked before providers see the enquiry. It even quotes the exact consent text.

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 dense and front-loaded with the purpose and exclusions, and every sentence contributes to correct usage. It is somewhat long and runs multiple steps into one paragraph, but the complexity justifies the length; a more bulleted structure could improve scannability.

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 two-step protocol, the consent requirement, nested answers, and the absence of any annotations, the description is thorough enough for an agent to call the tool correctly through both steps. It covers the outputs of step 1, the condition for step 2, and the downstream email behavior, leaving no critical invocation detail 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 meaningful meaning beyond the schema: answers must be keyed by field key from enquiry_fields, consent must be true only after the exact consent statement is accepted, and confirmation is the token from step 1. This elevates parameter understanding beyond mere names and types.

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 ('Submits an enquiry') and a clear resource ('Florida Solar Cost Calculator'), and explicitly distinguishes the tool from a purchase or guaranteed quote. This makes its purpose unambiguous and separates it from related tools like 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 two-step workflow is explicitly laid out: first call with answers and consent=true, show the summary, then call again only if the person agrees. It also references enquiry_fields, implying a dependency on that sibling. However, it does not explicitly say 'use calculate for quotes instead' or name alternatives directly, so the contrast with siblings is slightly implicit.

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