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

With no annotations, the description fully carries the transparency burden and does it well. It discloses that an enquiry is initiated with human providers, that nothing is bought or paid for, that no quote is guaranteed, and that the operation is free. It also tells the agent what information is returned, including consent wording and confirmation details.

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 contributes meaningful information, and key behaviors are stated plainly without padding. The structure moves from purpose to exclusions to return contents in a logical order.

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 no-parameter documentation tool with no output schema, the description is complete. It explains what the tool does, what the related submit_enquiry tool does, what behavioral caveats apply, and what information will be returned. An agent can confidently use this tool without additional context.

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 to document. The description adds value by explaining what the tool returns, which is more relevant than parameter details here. The baseline for a zero-parameter tool 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 purpose: this tool explains what submit_enquiry does, rather than performing the enquiry itself. It names the sibling tool it documents and clearly frames the tool as a read-first explanation. The title reinforces the purpose without being the only evidence.

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 words 'Read first' give clear usage guidance: read this before using submit_enquiry. It also sets expectations about what the sibling tool does not do, which helps an agent avoid misuse. It does not explicitly mention enquiry_fields, but the guidance is still contextually 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?

With no annotations present, the description carries the burden of explaining behavior. It clarifies that the tool returns field metadata rather than submitting anything, and it provides the relationship to submit_enquiry. However, it does not disclose whether this is a pure read operation, whether any network/cost implications exist, or what happens if the enquiry has no 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 compact sentences with no filler. The core content of the response is listed efficiently, and the key usage pointer to submit_enquiry is included 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 metadata tool, the description covers the output contents and how the result connects to a sibling tool. It is slightly light on explicit behavioral guarantees and sibling differentiation, but overall it gives an agent enough context to call the tool 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?

There are zero parameters, so the schema provides no parameter meaning to add. The description compensates by explaining that the returned field keys are used for submit_enquiry, which is the main semantic information an agent needs.

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 exactly what the tool returns: every field of the Malta Company Cost enquiry, including key, label, type, required status, help text, and options. It does not fully distinguish itself from the sibling enquiry_describe, though the detailed field-level focus and pointer to submit_enquiry make the primary purpose clear.

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 implies its usage by saying answers should be passed to submit_enquiry keyed by field key, which tells the agent this tool is the source for field keys. However, it does not explicitly say when to use enquiry_fields versus enquiry_describe, nor does it state any conditions or exclusions.

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: it discloses that step 1 only validates and returns a summary/consent line/token, that step 2 actually submits, and that the person must click an emailed link before any provider sees the data. It also spells out what consent authorises (up to three MFSA-licensed providers, per-firm notification, opt-out) — non-obvious side effects an agent could not infer.

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 prohibitions and the two-step flow are front-loaded and every procedural sentence earns its place. The one weakness is that the full consent sentence is reproduced verbatim from the consent field's schema description, a redundancy against structured data that lengthens an otherwise tight 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?

There is no output schema, so the description must describe returns — and it does: step 1 returns a summary, a consent line and a confirmation token. Together with the two-step gating and the email double-opt-in, an agent has everything needed to drive the flow correctly and safely.

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 real meaning beyond the schema: it tells the agent that answer keys come from enquiry_fields, and that the confirmation token must be the one returned in step 1 and supplied only after approval, which gives the ordering semantics of the fields rather than just their types.

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 to Malta Company Cost') and immediately demarcates what it is not ('NOT a purchase, NOT a guaranteed quote'), which is the key ambiguity for a commercial-intent agent. It also points to the enquiry_fields sibling as the source of answer keys, so it is distinguishable from its siblings without opening their schemas.

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 an explicit two-step protocol with the precondition for each call: step 1 with answers+consent to validate, step 2 only 'if the person agrees' with the confirmation token. It also states the human step in between (show the summary and consent line), leaving nothing to inference.

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