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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 behavioral disclosure burden. It does disclose one useful trait: missing inputs fall back to documented defaults. It does not explicitly state that this is a pure read-only calculation or what it returns, though the calculator nature makes that reasonably evident from the name.

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 short sentence with the main action front-loaded. But the typo 'calculator calculator' and the misleading input enumeration are waste, and the list does not earn its place because it conflicts with the schema.

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 six parameters, no output schema, and no annotations, the description should at least clarify what the calculator computes, what the expected output is, and how it relates to calculator_describe. None of that is present, and the mismatched input list increases confusion rather than reducing it.

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 schema covers all six parameters with descriptions and defaults (100% coverage), which normally establishes a baseline of 3. The description actively detracts, however, by listing inputs ('Electricity you buy each year', 'System size that covers it') that do not correspond to the schema's ppw, bill, rate, orient, battery, and battCost, potentially misleading an agent about what to pass.

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 resource ('California solar cost calculator'), so an agent can roughly tell what it does. However, the redundant 'calculator calculator' phrasing and an input list (kWh, kW, panels) that does not match the actual schema (ppw, bill, rate, orient, battery, battCost) muddle the statement. It also does not differentiate this 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?

No guidance is given on when to use this tool versus the siblings (calculator_describe, submit_enquiry, etc.). The only usage hint is that missing inputs fall back to their documented defaults, which is useful but does not address alternative selection 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?

No annotations are provided, so the description carries the burden of disclosing behavior. It indicates the tool returns a description of inputs, outputs, and assumptions, which implies a read-only informational operation, but 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 names the three major content areas: inputs, outputs, and assumptions/tables. It is concise, front-loaded, and every part 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 simple informational tool with no parameters and no output schema, the description covers the essential content scope. It could be slightly more explicit about being a read-only reference and about not performing the calculation, but overall the agent can correctly understand what this tool offers.

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 the input schema is empty. The baseline for a zero-parameter tool is 4, and the description appropriately does not need to explain parameters. It promises details about inputs, but those are content described by the tool, not calling 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 describes the calculator's inputs, outputs, and underlying assumptions/tables. This differentiates it from the sibling 'calculate' tool, which presumably executes the calculation, though the description does not explicitly name the alternative.

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 guidance is given about when to use this tool versus the sibling 'calculate' or 'enquiry_describe' tools. The intended use is implied by the name and title, but the description does not state conditions such as 'use this before calculating' or 'use calculate to run the calculator.'

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 of behavioral disclosure. It explains exactly what the tool does (returns a plain-language explanation of submit_enquiry), what it does not do (nothing is bought, ordered, paid, or guaranteed), and what information is returned (who receives details, consent wording, and confirmation method). This is thorough for a read-only informational 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 three sentences, front-loaded with the most important instruction ('Read first'), and every sentence earns its place: it states the tool's purpose, clarifies what it is not, and summarizes the return value. There is no fluff or redundant 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?

Given the simple nature of the tool (zero parameters, no output schema), the description is fully complete. It explains what the tool does, why an agent should read it first, what the returned information covers, and the key caveats about submit_enquiry. Nothing essential is missing for an agent to decide when and how to invoke this tool.

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 correctly focuses on the tool's informational output rather than parameter syntax, and no additional parameter details are needed. It fully compensates for the absence of parameter information by explaining the tool's behavior.

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 ('States plainly') and resource ('what submit_enquiry does on California Solar Cost Calculator'), and clearly differentiates the tool from its sibling submit_enquiry by emphasizing it is informational rather than an action. It also clarifies that no purchase, order, payment, or guaranteed quote is involved, leaving no ambiguity about the tool's role.

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' explicitly tells the agent when to use this tool: before engaging with submit_enquiry. It provides clear context that this is a prerequisite read, though it does not explicitly mention exclusions or alternatives beyond the implied distinction from submit_enquiry. This is strong guidance for a describe-style 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, the description carries the burden of behavioral disclosure. It clearly explains what information is returned: key, label, type, required flag, help text, and allowed options. It does not explicitly say the operation is read-only, but the content strongly implies a metadata retrieval with 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 two sentences with no wasted words. The first sentence enumerates exactly what the agent will receive, and the second sentence gives direct actionable guidance for the related submission tool.

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 listing tool, the description is sufficiently complete. It identifies the domain, the exact fields returned, and how the output should be used with submit_enquiry. It could mention the output format or whether the result is a list, but that is a minor 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?

The tool has zero parameters, so there is no parameter semantics burden on the description. The baseline of 4 applies because there is nothing to document and the description appropriately avoids inventing unnecessary parameter details.

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 returns every field of the California Solar Cost Calculator enquiry along with their metadata, which names a clear resource and distinguishes it from the sibling tools like submit_enquiry and calculate. It does not use a strong verb like 'list' or 'get', but the meaning is unambiguous.

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 context: use this tool to discover enquiry fields and pass answers keyed by field key to submit_enquiry. It does not explicitly exclude other tools or state when to prefer enquiry_describe, but the relationship to submit_enquiry is clearly implied.

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 disclosure burden, and it does so thoroughly. It reveals that the tool is two-staged, that validation produces an intermediate summary, that a confirmation token is needed for final submission, and that the person must click an emailed link before any provider sees the enquiry. It also discloses the exact consent text, eliminating ambiguity about what 'consent' means.

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 but every sentence earns its place. It front-loads the core purpose and the crucial 'not a purchase' caveat, then organizes the two-step flow clearly. The quoted consent line is necessary verbatim text, not padding.

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 annotations and no output schema, the description is remarkably complete. It explains all three parameters, the two required invocation patterns, the intermediate output (summary, consent line, token), and the post-submission email behavior. An agent has everything needed to call the tool correctly and avoid the common mistake of treating it as a single-step purchase.

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 semantic value beyond the raw schema. It explains that answers must be keyed by enquiry_fields keys, that consent must reflect the exact quoted agreement, and that confirmation is the token returned from Step 1 and reused in Step 2. These details transform the parameter names from generic placeholders into a coherent workflow.

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 opens with a specific verb and resource: 'Submits an enquiry to California Solar Cost Calculator.' It immediately distinguishes itself from related actions with 'NOT a purchase, NOT a guaranteed quote,' and clearly frames the tool as a two-step human-provider submission process. This separates it from sibling tools like calculate or enquiry_describe without ambiguity.

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 step-by-step usage instructions: Step 1 requires answers plus consent=true and returns a summary and confirmation token; Step 2 is only invoked if the person agrees and requires the same answers, consent=true, and the confirmation token. It also references enquiry_fields for the answer keys, providing concrete orientation to the sibling tool that supplies the required field structure.

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