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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 burden of behavioral disclosure. It only restates the tool's subject matter in noun form and says nothing about whether this reads data, what output is returned, or any side effects. This is effectively no behavioral 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 a single short sentence, but it is under-specified rather than efficiently concise. It lacks a verb, actionable content, and any structural signposting, so it does not earn its place as a useful tool definition.

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?

With no output schema and no annotations, the description should explain what the tool returns or how the criteria are presented. It does neither, leaving the agent without enough information to invoke the tool confidently or interpret its result.

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 schema description coverage is 100%, so the baseline for a zero-parameter tool applies. The description does not need to explain parameter details because there are none.

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 resource: 'the criteria and any filters' of the Routes to Mexican manufacturing capacity comparison. It is clear in subject matter but uses a noun phrase rather than a verb and does not explicitly distinguish it from sibling tools like compare_options or compare_table.

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 about when to use this tool versus its siblings. It does not mention compare_options, compare_table, or any conditions that would select this tool, leaving the agent to infer usage from context.

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 burden of explaining behavior. It only mentions optional filtering and the fields contained; it never states that the operation is read-only, what the response looks like, or any side effects. The behavioral profile is largely left to inference.

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, compact sentence that front-loads the resource and then adds the filter option. It is readable and contains little wasted text.

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 no annotations, no output schema, and two undocumented parameters, the description is too thin. It does not sufficiently explain the tool's behavior, return value, or parameter semantics, so an agent would lack essential information to invoke 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 0% for two undocumented string parameters (filterKey, filterValue). The description's phrase 'filtered by a tag value' hints at filterValue but never explains filterKey or how the two parameters relate, leaving a critical mapping gap.

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 is a noun phrase: 'The options in the Routes to Mexican manufacturing capacity comparison...' It identifies the resource and its fields but never states an action like 'list' or 'returns'. This makes the purpose somewhat inferable but vague, and it does not distinguish the tool from siblings such as compare_criteria or compare_table.

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 compare_options versus the sibling tools. The only conditional phrase, 'optionally filtered by a tag value,' speaks to parameter behavior, not to tool selection or context.

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 describes the output content but does not mention how the optional 'option' parameter changes behavior, whether this is a safe read-only operation, or what the response shape looks like.

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 focused sentence with minimal waste. It front-loads the core output content, though the long phrase 'Routes to Mexican manufacturing capacity comparison' could have been simpler.

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 simple with one optional parameter that the schema already documents. However, without an output schema, the description does not explain what the returned table looks like or what happens when 'option' is provided versus omitted, leaving some ambiguity.

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 already describes the single parameter ('one option's name, else all') with 100% coverage. The description adds no additional parameter semantics, so the baseline score 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 clearly states what the tool returns: each option's value on every criterion in the comparison, framed as the full table. This gives an agent a concrete sense of the tool's output without needing to open 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?

No explicit guidance is given about when to use this tool versus siblings like compare_criteria or compare_options. The phrase 'full table' hints at its role, but the description never states conditions, exclusions, or 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 carries the burden of behavioral disclosure. It does disclose what the tool returns and clarifies that an enquiry is free and not a guaranteed purchase. However, it never explicitly states that calling this describe tool itself has no side effects, which matters when no read-only hint is present.

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?

Three short sentences with the most important instruction ('Read first.') at the very beginning. Every sentence adds value: it names the sibling, explains the boundary, and summarizes the return content 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 zero-parameter informational tool with no output schema, the description covers purpose, usage order, key concepts, and what is returned. It does not describe return formatting, but that is not essential for a conceptual explainer 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 there are no parameter semantics to document. The description correctly focuses on what the tool communicates rather than arguments, matching the baseline for a parameterless tool.

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 plainly what the tool does: it explains what submit_enquiry does on Made in Mexico Suppliers, and it names the specific domain and sibling. It also distinguishes itself with 'not a purchase, not a guaranteed quote,' so an agent can tell this description tool apart from the actual submission action.

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 leads with 'Read first,' clearly telling the agent to use this before interacting with submit_enquiry. It explains what the agent will learn (receivers, consent wording, confirmation), but it does not explicitly contrast this with other siblings like compare_options or enquiry_fields.

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 supplied, the description carries the behavioral burden. It is transparent about the returned content, but it does not explicitly state that the operation is read-only, whether authentication is required, or whether any side effects occur.

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 dense sentence front-loads the scope with 'Every field...' and then lists all relevant metadata attributes plus a downstream usage hint. There is no repetition of schema content and 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?

Given the zero-parameter input and the absence of an output schema, the description adequately explains what the tool returns and how to consume it. It does not specify the exact response container, but the listed attributes and keyed-answers note are sufficient for correct invocation.

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 has zero parameters, so the baseline is high and little parameter detail is needed. The description adds useful linking semantics by explaining that answers should be keyed by field key, connecting this tool's output to submit_enquiry's expected input.

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 is clear about what the tool exposes: every field of the enquiry, including key, label, type, required status, help text, and options. It does not use an explicit verb like 'list' or 'return', so it falls slightly short of the strongest level of purpose clarity.

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?

It gives clear usage context: retrieve the field metadata and pass answers to submit_enquiry using the field keys. It does not explicitly contrast this with enquiry_describe or other sibling tools, so it lacks full when-not-to-use guidance.

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 disclosure burden, and it does so thoroughly. It reveals that the first call only validates and does not submit, that the second call submits, that the person must click an emailed link before providers see anything, and it defines consent with the exact wording.

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 efficient, using numbered steps to convey the two-phase flow without wasted words. The consent quote and email-link caveat are necessary legal and behavioral details, not 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 tool with no annotations and no output schema, the description is complete enough for an agent to select and execute it correctly. It covers purpose, boundary conditions, the two-step invocation sequence, the meaning of consent, the confirmation token, and the downstream dependency on an email click.

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 the schema already describes the parameters, the description adds crucial operational meaning: answers must be keyed by field key from enquiry_fields, consent requires the exact quoted consent line, and confirmation is the step-1 token used to complete submission after approval. This goes well beyond the schema's minimal 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?

The description explicitly states the verb ('submits an enquiry'), the resource ('Made in Mexico Suppliers'), and immediately disambiguates the tool from a purchase or guaranteed quote. The two-step flow is also front-loaded in the title and first sentence, so an agent can clearly distinguish this from the sibling enquiry_describe and enquiry_fields 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 description provides a precise call protocol: step 1 with answers and consent=true to validate and obtain a token, then step 2 only after the person agrees and with the same answers plus the token. It also states when not to use it ('NOT a purchase, NOT a guaranteed quote') and references enquiry_fields for the correct answer keys.

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