ReciboPro Invoices

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

Annotations declare the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false), and the description adds genuinely useful context beyond them: nothing is ever sent, a review link is produced, and the user completes sending. It doesn't cover rate limits or failure behavior, but the review-before-send model is well disclosed.

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 core purpose and the no-send guarantee front-loaded, followed by content restrictions. 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?

No output schema exists, and the description explains the return (a private review link) and the no-send semantics, which is what an agent most needs. Given 10 undocumented parameters, it could say more about the optional fields, but the essential behavior is complete.

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 description coverage is 0% across 10 parameters, so the schema documents structure but not meaning. The description constrains what data may go into the invoice (user-stated prices/taxes/client details, no links or institution names), which is real guidance, but it never addresses individual parameters such as currency, language, due_date, or tax_rate.

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 ('Builds an invoice draft') plus the concrete outcome ('returns a private link where they review it and send it themselves'). This is clearly distinguishable from the sibling get_supported_options.

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 content constraints ('Only use prices, taxes and client details the user gave. Links, bank/tax-authority/payment-brand names are not allowed') that define when and how to use it. It stops short of naming an alternative tool or stating exclusions relative to siblings, but the operating conditions are 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only that the payload contains supported currencies and invoice languages — useful given there is no output schema, but no ordering, format, or other behavioral context.

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 front-loaded sentence with no filler; the resource being listed comes before any qualification. Nothing could be trimmed without losing meaning.

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, read-only reference lookup with no output schema, naming the returned content is sufficient to call it correctly. The only gap is that the exact response shape is unspecified, though the annotations make the operation low-risk.

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 there is no parameter semantics to explain; baseline 4 applies. Nothing in the description conflicts with the empty object schema.

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 ('Lists') and two concrete resources (currencies, invoice languages) scoped to the ReciboPro product. This is unmistakably distinct from the only sibling, create_invoice_draft, which is a write operation.

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 only says what the tool returns; it never says when to call it, e.g. before create_invoice_draft to discover valid currency/language codes, and gives no exclusions or prerequisites. Usage is left entirely to inference.

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