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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, and it delivers: it states what the tool returns, clarifies that nothing is bought, ordered, or paid, that no quote is guaranteed, that it is free, and that the response includes recipient details, consent wording, and confirmation behavior. This is highly transparent.

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 most important instruction ('Read first'). Every sentence adds distinct value: what the tool does, the key caveats, and what the returned content covers. 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?

Given zero parameters, no annotations, and no output schema, the description fully explains the tool's purpose, return content, and semantic boundaries. Nothing critical is missing for an agent to decide whether and when to call 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 tool has zero parameters, so there are no parameter semantics to document. The schema coverage is 100% and the description needs no parameter details; the baseline of 4 applies.

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'), and clearly distinguishes this tool from the sibling submit_enquiry tool. It also explains the core semantic distinction: an enquiry with human providers, not a purchase or guaranteed quote.

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 an explicit context cue: this tool should be used before submitting an enquiry. It does not explicitly name the alternative tools or say when not to use it, but the context is clear enough for an agent to know this is preliminary/descriptive rather than an action 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 but is mostly a structural description of the output. It does convey that this is a read-only metadata tool and implies no side effects, but it does not mention whether the field values or options are localized, whether the schema corresponds to a specific step, or what happens for conditional fields.

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?

Two sentences, no filler. The first sentence is front-loaded with what the tool returns; the second sentence gives actionable guidance on using the result. Every sentence 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 zero-input metadata tool, the description is nearly complete: it explains what is returned and how to use it. It is slightly short on guidance for choosing this versus enquiry_describe, but the field-level detail in the description largely makes the tool self-sufficient.

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 takes zero parameters, so parameter semantics are inherently simple. The description correctly avoids inventing parameters and makes clear that the answer to how to use it is through the returned field keys, which is meaningful context.

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 the tool as returning every field of a specific enquiry, enumerating what is included: key, label, type, required flag, help text, and allowed options. It distinguishes itself from siblings by being the field-schema/metadata tool for a Conveyancing Fees Ireland enquiry.

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 explicitly says to pass answers to submit_enquiry keyed by field key, which tells the agent how to use the output. It does not explicitly state the alternative is enquiry_describe or when to use that instead, so it lacks direct 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 burden — and it delivers: the two-step call behavior, the confirmation token handoff, the email-activation requirement before any provider sees the enquiry, and the exact consent wording are all disclosed. An agent knows precisely what preconditions and side effects each call has.

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 earns its length: every clause carries procedural or exclusionary information, and the Step 1/Step 2 structure makes it scannable. Minor redundancy with the title ('two steps; not a purchase') keeps it from a 5.

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 stateful two-step tool with no output schema and no annotations, the description is complete: it explains the step-1 return values (summary, consent line, token), the condition for step 2, and the email link the person must click. Nothing an agent needs to drive both calls 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; the description adds meaning on top by tying the answers object to 'field key from enquiry_fields' and explaining that the confirmation property is the step-1 token. Consent semantics are reinforced with the exact user-facing wording.

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 — submitting an enquiry to Conveyancing Fees Ireland — and immediately disambiguates it from a purchase or guaranteed quote. It also names the two-step interaction model, which distinguishes this submission tool from the sibling tools 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?

The two-step protocol is explicit: step 1 validates and returns a token, and step 2 is only for after the person agrees, using the same answers plus the token. It gives clear when-not context ('NOT a purchase') but does not explicitly route the agent to sibling tools like enquiry_fields for obtaining the field keys.

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