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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 behavioral disclosure burden. It makes the tool's informational, read-only nature clear by saying it 'states' and 'returns' content, and it details what that content is. It does not add an explicit 'no side effects' line, but that is strongly implied for a descriptive 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 tight sentences, front-loads the most important instruction ('Read first'), and every remaining sentence adds substance: what it explains, what it does not involve, and what it 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 0-parameter tool with no output schema, the description fully covers what an agent needs: the relationship to submit_enquiry, the content returned, and the reassurance about no purchase, payment, or guaranteed quote. Nothing essential is missing for correct selection and 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 input schema has zero properties and 100% schema coverage, so there are no parameters to document. The description appropriately spends no space on parameter semantics, matching the baseline for a 0-parameter 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?

The description uses a specific verb and resource: it 'states plainly what submit_enquiry does' and enumerates the returned content. It clearly distinguishes this meta-explanatory tool from actually submitting an enquiry, and its relationship to submit_enquiry is explicit.

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 opens with 'Read first,' which gives an explicit usage directive and positions the tool as the precursor to submit_enquiry. It does not explicitly discuss when not to use it or mention the enquiry_fields sibling, but the intended workflow placement 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?

There are no annotations, so the description carries the full burden. It discloses what data is returned and how it connects to submit_enquiry, implying a read-only metadata lookup. However, it does not explicitly state that the tool has no side effects, does not describe the response format, or mention any access considerations.

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 front-loaded, starting with 'Every field of the Oklahoma Foundation Repair Cost enquiry' and immediately enumerating the included metadata. The follow-up instruction about submit_enquiry is a single, purposeful sentence 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 a zero-parameter metadata retrieval tool with no output schema, the description sufficiently explains what the agent will receive and how to use it downstream. It covers the practical need: know the field keys, required status, help text, and options before submitting an enquiry.

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; the baseline of 4 applies. The description adds useful semantic context by explaining that the returned field keys should be used as keys when submitting answers, which connects the output to the sibling 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?

The description clearly states what the tool provides: every field of the Oklahoma Foundation Repair Cost enquiry, including key, label, type, required status, help text, and options. The title reinforces this by calling out 'the questions the enquiry asks.' It differentiates from submit_enquiry by focusing on field metadata, though it does not explicitly distinguish itself from 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?

The instruction 'Pass answers to submit_enquiry keyed by field key' gives clear, actionable context for when to use this tool: before submitting an enquiry. It does not explicitly state when not to use it or name alternatives, but the connection to submit_enquiry is a strong usage signal.

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 behavioral burden and does so richly: it discloses what each step returns, that a confirmation token gates submission, that no provider sees the enquiry until the person clicks an emailed verification link, the scope of consent (up to three contractors), and how to stop further sharing.

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?

Front-loaded with the key differentiator (not a purchase) and cleanly organized into Step 1 / Step 2. The verbatim consent sentence is long, but it is the literal text the agent must display, so it earns its length rather than being 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?

There is no output schema, and the description compensates by describing what each step returns (validated summary, consent line, confirmation token) as well as the downstream double opt-in email. Nothing an agent needs to complete both calls 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 workflow meaning beyond the schema: answers must be keyed by field key from enquiry_fields, consent must be true, and confirmation is only supplied in the second call after the person approves the summary. This sequencing context is not evident from the field descriptions alone.

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 a specific verb and resource (submits an enquiry) and immediately disambiguates it from adjacent concepts with 'NOT a purchase, NOT a guaranteed quote'. The named recipient ('Oklahoma Foundation Repair Cost', human providers) and the two-step nature make it distinguishable from the sibling tools at a glance.

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?

Gives explicit when-to-use sequencing: Step 1 with answers+consent, then 'only if the person agrees' Step 2 with the token. It also routes the agent to the sibling enquiry_fields for field keys, so both the condition and the alternative source of data are named.

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