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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully reveals what the tool computes (low/high/installed cost estimates), what the 'system size used' output is, and that missing inputs fall back to schema defaults. It does not explicitly state read-only or side-effect-free behavior, but for a calculator this is strongly implied and the disclosed outputs are sufficient.

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 with a compact, front-loaded action and list-style outputs. The phrase 'calculator calculator' is a minor redundancy/typo that slightly detracts, but overall the description is appropriately sized with no filler.

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?

The tool is a simple, unparameterized calculator with no output schema, and the description compensates by listing the expected outputs and the default-fallback behavior. It does not explain return-value formatting, but that is not necessary given the absence of an output schema and the tool's straightforward nature.

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 fully documents bill, size, credit, and battery. The description adds no new parameter-level meaning; 'System size used (kW)' is presented as an output, not a parameter clarification. This matches the baseline of 3 for high schema coverage.

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 ('Run the Texas solar cost calculator') and enumerates the outputs it produces (low estimate, high estimate, installed cost midpoint), which goes beyond the tool name and title. It does not explicitly contrast itself with sibling tools like calculator_describe, but the verb 'calculate' and the output list make its role reasonably distinct.

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 on when to use this tool versus alternatives such as calculator_describe or submit_enquiry. It only mentions default fallback behavior ('Missing inputs fall back to their documented defaults'), which is a behavioral note rather than usage direction.

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. It clearly indicates the tool is informational and describes inputs, outputs, assumptions, and tables. It does not explicitly state that no calculation is performed, but 'describes' strongly implies non-mutating 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?

The description is a single dense sentence that front-loads the key subject and enumerates the covered content without 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 describe-style tool with no output schema, the description covers the essential scope: inputs, outputs, assumptions, and tables. It could be slightly stronger by explicitly distinguishing itself from 'calculate', but that gap is reflected in the usage guidelines.

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 are no parameter details for the description to add beyond the schema. The description does usefully signal that the tool itself explains input 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 the tool describes the calculator's inputs, outputs, assumptions, and tables, which is a specific verb-resource pairing. It is clear what it does, but it does not explicitly differentiate itself from sibling 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?

Usage is implied: an agent would invoke this to understand the calculator rather than to run a calculation. There is no explicit statement of when to use this versus 'calculate' or the enquiry tools.

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 disclosure burden. It conveys that the tool is informational by stating it 'returns who receives the details, the consent wording, and how the person confirms,' and it clarifies what the underlying action does not do. It does not explicitly say 'this tool has no side effects,' but the return-focused wording implies a read-only description.

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 with the key instruction: 'Read first.' Every sentence adds distinct value: what the underlying tool does, what it does not do, and what this describe tool returns. There is no filler.

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 describe/meta tool with no parameters and no output schema, the description is complete. It tells the agent what the tool returns and explains the key facts about the associated submit_enquiry action, including consent and confirmation, so an agent can 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 baseline is 4. The schema coverage is vacuous, and the description appropriately focuses on what the tool returns rather than parameter details, which are unnecessary 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 states exactly what the tool does: it explains what submit_enquiry does, and explicitly contrasts it with a purchase or guaranteed quote. This clearly identifies the resource (the enquiry action) and distinguishes the tool from the sibling calculator and submission 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 opening instruction 'Read first' provides a clear usage context: this is a prerequisite overview for submit_enquiry. It does not explicitly mention sibling alternatives like calculator_describe or enquiry_fields, but the 'Read first' framing gives the agent enough guidance on when to invoke 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 behavioral disclosure burden. It does convey that this is a metadata/field-listing operation and that its keys feed into submit_enquiry, implying a read-only, non-mutating behavior. However, it does not explicitly state that it performs no submission, makes no changes, or describe how the field data is returned.

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 and well-structured: the first sentence states what is included, and the second provides actionable usage guidance. It contains 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 zero-parameter metadata tool with no output schema, the description is largely complete: it specifies the fields and properties returned and connects the tool to the sibling submit_enquiry workflow. It could mention response format or ordering, but those are minor gaps for a field-listing utility.

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; there is no input schema for the description to compensate for. The description adds useful semantic meaning by highlighting the 'key' field and how it maps to submit_enquiry 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 clearly identifies the tool as exposing every field of the Texas Solar Cost Calculator enquiry and enumerates what each field definition contains: key, label, type, required, help text, and options. It is distinguishable from siblings by focusing specifically on enquiry field metadata, though it lacks an explicit verb like 'returns' or 'lists'.

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 a clear usage cue: the field keys returned should be used when passing answers to submit_enquiry. This gives practical context for when the tool is useful, even though it does not explicitly compare against enquiry_describe or calculate.

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 validation, what step 1 returns (summary, consent line, token), that step 2 actually submits, that the person gets an email with a click link, and that providers only see the enquiry after that click. It even quotes the exact consent statement.

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 longer than average but every sentence earns its place: the caveat is front-loaded, then step 1 and step 2 are clearly delineated, and the consent text is given verbatim. The structure mirrors the call sequence, which makes it easy for an agent to follow.

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 two-step submission tool with no output schema, this description is remarkably complete. It explains both calls, what to show the user between steps, the required confirmation token, the email click-through, and the consent condition. No practical detail needed for correct invocation 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful usage semantics beyond the schema: answers must be keyed by field key from enquiry_fields, the confirmation token comes from step 1, and consent must match the exact quoted consent line. This adds practical value over the raw property descriptions.

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?

Description states the exact verb ('Submits an enquiry') and target resource (Texas Solar Cost Calculator), and immediately clarifies what it is not ('NOT a purchase, NOT a guaranteed quote'). This clearly distinguishes it from sibling tools like calculate, enquiry_describe, and 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?

Provides a precise two-step calling protocol with explicit conditions: call first with answers and consent=true, then call again only if the person agrees, including the confirmation token. It does not explicitly name alternatives or when-not-to-use, but the step conditions and consent gate are clear enough for correct invocation.

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