ReciboPro Invoices

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

Annotations already declare readOnlyHint=false, idempotentHint=true and destructiveHint=false, but the description adds the critical behavioral distinction that it never sends anything and hands back a private review link. It still omits error behavior and any auth/permission requirements, so it is strong but not exhaustive.

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, front-loaded with what the tool does and the returned artifact, then the constraints. Every sentence earns its place with 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 10-parameter, no-output-schema tool the description covers purpose, behavior and input constraints well, but leaves all parameter semantics undocumented at 0% schema coverage. An agent can pick the tool but still lacks guidance on how to fill the schema 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?

Schema description coverage is 0% across 10 parameters, so the description carries the full burden, yet it adds no per-parameter meaning. It vaguely gestures at 'prices, taxes and client details' without mapping to unit_price, tax_rate, client_name, due_date, or the currency/language enums, leaving the agent to infer everything from the raw 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 and resource ('Builds an invoice draft') and further clarifies the output ('returns a private link'). It is clearly distinguishable from the sibling get_supported_options, which would be a lookup rather than a creation tool.

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 concrete input constraints ('Only use prices, taxes and client details the user gave', no links or bank/tax-authority/payment-brand names) and clarifies the draft-vs-send boundary. It does not, however, reference the sibling get_supported_options or say when to consult it (e.g. for valid currency/language values), so routing guidance is incomplete.

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.