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

With no annotations, the description carries the full burden. It discloses that nothing is bought, no quote is guaranteed, and it's free, which clarifies the read-only and non-committal nature. It also states what the tool returns, making its behavior transparent. It doesn't explicitly state it's a read operation, but the context implies it. No contradiction with annotations (none exist).

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, front-loaded with the key instruction 'Read first,' and each sentence serves a purpose: stating the tool's role and detailing what it returns. It's efficient and avoids redundancy, with no wasted words.

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 an informational tool with no parameters and no output schema, the description is fully complete. It explains the tool's purpose, its content (what it returns), and its behavioral implications (free, no guarantee). Nothing an agent needs to correctly invoke or interpret this tool 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 and 100% schema coverage (empty schema), so there's nothing to document. The description adds value by explaining what the tool returns, which compensates for the lack of params. The baseline of 4 is appropriate, as the description enriches the user's understanding of the tool's output without needing to discuss 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 explicitly states the tool's purpose: to read first and understand what submit_enquiry does. It clearly distinguishes itself from siblings by framing itself as a meta-tool that explains the submission process, not the submission itself. The verb 'describes' and resource 'submit_enquiry' are specific and 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 opening 'Read first' gives explicit usage guidance, implying it should be consulted before submit_enquiry. It also clarifies what the tool returns (recipient details, consent wording, confirmation method), which helps the agent decide when to call it. However, it doesn't explicitly mention when not to use it or how it compares to enquiry_fields, leaving a slight gap in routing.

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 transparency burden. It states exactly what metadata is returned and, by pointing to submit_enquiry for sending answers, implies this tool is a read-only lookup rather than a submission action. It could explicitly state 'read-only' or 'does not submit', but the wording is sufficient for this metadata 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 two sentences with no wasted words. The first sentence front-loads the complete set of returned field attributes, and the second gives the actionable relation to submit_enquiry.

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 covers what an agent needs: the field metadata contents and how to use the results with submit_enquiry. 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 input schema is empty and has 100% coverage, so there are no parameters to document. The description adds semantic value by explaining that the field keys are the connection to submit_enquiry, which goes beyond what the empty schema can provide.

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's resource: every field of the Saudi Company Setup Cost enquiry, including key, label, type, required status, help text, and allowed options. It also distinguishes itself from submit_enquiry by instructing that answers should be passed there keyed by field key, 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 downstream usage instruction: use the field keys to pass answers to submit_enquiry. However, it does not explicitly state when to choose this tool versus the sibling enquiry_describe, leaving some inference to the agent.

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 and meets it: validation behavior, what step 1 returns (summary, consent line, confirmation token), what the user must do before providers see anything (click an emailed link), and the exact scope of consent (up to three agents, contacted directly, opt-out). This is exactly the context an agent needs to avoid submitting prematurely.

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 two-step flow is front-loaded and every operational sentence earns its place. The one redundancy is the verbatim consent text, which is duplicated in the schema's consent description, though repeating it is defensible since the agent must display it.

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 multi-step, consent-gated submission tool with a nested object parameter and no output schema, the description covers the full lifecycle: inputs, validation, return artifacts, second call, and downstream email confirmation. Nothing an agent needs 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?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning beyond the schema: the answers object must be keyed by field key obtained from enquiry_fields, and the confirmation token is specifically the value returned from step 1 after approval. It clarifies the token's provenance and lifecycle, which the schema alone does not.

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 ('submits an enquiry to Saudi Company Setup Cost') and immediately bounds it with what it is NOT ('NOT a purchase, NOT a guaranteed quote'). The two-step structure further disambiguates it from the discovery siblings enquiry_fields 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?

It gives explicit when-to-use instructions for both invocations: Step 1 with answers + consent=true, Step 2 only if the person agrees, with the token. It also names the dependency on enquiry_fields for the answer keys, so the agent knows the sequencing relative to siblings.

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