Translayte

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

With only openWorldHint in annotations, the description carries the burden well. It discloses that links expire after 48 hours, that pay_url is the payment page and status_url collects documents, that existing-email customers receive links by email instead, and that idempotency_key prevents duplicate orders on retry.

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 front-loaded with the core action and response behavior, and nearly every sentence earns its place by explaining links, email fallback, document flow, or idempotency. It is dense as a single paragraph and one sentence about document upload timing is slightly convoluted, but overall it is efficient.

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 complex 14-parameter mutation with no output schema, the description covers the essential context: customer identity, quote-derived arguments, payment and status links, 48-hour expiry, email fallback, document handling, and duplicate-order prevention. An agent has enough detail to invoke it correctly and explain next steps to the customer.

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 100%, so the schema already documents all 14 parameters in detail. The description adds a useful relationship to get_quote and send_document, but most parameter-level details such as E.164 phone, file_tokens, quantity, and idempotency_key are already covered by the 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?

The description states a specific verb and resource: "Places an unpaid order for the customer." It also distinguishes the tool from get_quote by explaining that create_order takes the same arguments plus customer identity details, so an agent can understand exactly what this tool does.

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 gives clear workflow guidance: send documents first with send_document, or let the customer upload them at status_url after paying when creating from a page count. It also explains the email-account case and idempotency-key retry behavior. It does not explicitly say when not to use this tool, but the operational context is strong.

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?

The readOnlyHint annotation already establishes the safe read profile. The description adds useful behavioral context about the coverage data returned and explains that non-covered locations require a quote request via the order form, though it does not disclose whether the data is static or cached.

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 front-loaded and compact, with no filler. It is a single dense sentence with semicolons that could be easier to scan, but every clause carries substantive coverage information.

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?

With no input parameters, no output schema, and readOnlyHint=true, the description carries most of the burden for explaining what comes back. It adequately describes the coverage categories and the quote-request fallback, though it leaves the exact response structure implicit.

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 are no parameter semantics to explain and the baseline is 4. The description does not need to compensate for any schema gaps.

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 defines the resource as service coverage and enumerates what it returns: language/certification availability, country authorities, notarisation and apostille/legalisation routes, formats, turnaround, and online pricing vs quote. It is specific but does not explicitly distinguish itself from siblings like list_countries or list_services.

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?

Usage is implied: use this to check where services are available, and 'Anywhere else is a quote request through the order form' suggests the fallback path. However, it does not explicitly say when to use this instead of list_countries, list_languages, list_services, or get_quote.

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 readOnlyHint already given, the description adds the valuable traits: it discloses returned fields, the enumerated next actions (pay, upload_documents, wait), and that links come back fresh on each call. It is consistent with the read-only annotation but says nothing about expired/invalid links or error behavior.

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, front-loaded with the core purpose and ending on the credential constraint that governs correct invocation. The mid-sentence field list is dense but every item maps to something the agent must interpret on return.

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?

With no output schema, the description carries the return-value burden and does so by enumerating the status fields and the possible next actions. What's missing is failure handling — what happens if the URL is tampered with or stale — which the sibling recover_order_links hints is a real scenario.

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 would be 3, but the description genuinely upgrades the single parameter by calling it 'signed' and framing it as the sole credential ('nothing else identifies an order'). That security-semantics detail is not present in the schema text and changes how an agent treats the argument.

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 the resource precisely ('where an order stands') and enumerates the returned facets (status, payment, balance, due date, documents, next action), so an agent knows exactly what it gets. It lacks an explicit verb and never names a sibling, so the contrast with create_order or recover_order_links must be inferred from the schema reference.

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 gives a clear precondition — you must already have the signed status_url — and states the hard constraint that 'the link is the credential; nothing else identifies an order'. It does not name recover_order_links as the fallback when the link is lost, so the exclusion path for that case is left implicit.

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 only declare readOnlyHint=true, so the description must carry the rest — and it does, disclosing the exact return shape: ex-VAT lines, VAT, total, every certification the pair offers with its total, a delivery estimate, and an order_url. That is real value beyond the annotation. It stops short of auth requirements or any note about pricing staleness.

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?

It is a single ~60-word sentence stitched together with colons and commas, packing the purpose and the full return-value inventory into one run-on clause. The core purpose is front-loaded, but the trailing list of outputs is dense and hard to scan; splitting it into two or three sentences would cost nothing.

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?

With no output schema, the description is the only source of return-value information, and it covers that well (line items, VAT, total, all certification totals, delivery estimate, order_url). Nine parameters are fully documented in the schema and the read-only nature is covered by the annotation, so what remains missing is only minor: no indication of required permissions or when a quote might be unavailable.

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% and the parameter descriptions are already rich (speed surcharges, per-currency price sheets, quantity-vs-file_tokens measuring rule, omitting certification to list all options). The description only restates those axes in prose and adds no syntax, format, or edge-case detail beyond the schema, so the baseline 3 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 names the resource precisely — a price quote for a certified translation — and enumerates the dimensions that drive the price (language pair, page count or sent documents, speed, certification, currency). It implicitly separates itself from create_order by pointing at 'the order_url for the website checkout' rather than claiming to place an order, though it never names a sibling explicitly.

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?

Usage is implied rather than stated: 'the same calculator as checkout' suggests you call this to price something before ordering, and the mention of 'the documents sent with send_document' hints at the file-token workflow. But there is no explicit when-to-use clause, no statement that this does not create an order, and no routing to create_order or list_languages.

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 only declare readOnlyHint=true; the description adds substantive behavioral context by naming the per-country attributes returned, including the three-state pricing model (priced online, quoted, or not offered). It omits anything about result size, ordering, or whether unsupported countries appear, so it stops short of full transparency.

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 dense sentence, front-loaded with the key fact (ISO country codes) and then the field meanings; nothing is redundant. The nested relative clauses for pricing make it slightly harder to parse than it needs to be.

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?

With no output schema and no parameters, the description carries the burden of explaining return values, and it does so adequately by enumerating the flags per country. Remaining gaps are minor: no indication of how many countries are returned or whether the list is filtered to supported countries only.

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?

Zero parameters, so the baseline is 4, and the description goes further by tying the returned codes to the specific sibling-tool parameters (country_of_use, customer_country), clarifying expected value format indirectly via the ISO 3166-1 alpha-2 reference.

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 the resource precisely (ISO 3166-1 alpha-2 country codes) and enumerates the metadata attached to each entry, so an agent knows this is a country lookup with apostille/sworn-translation/pricing flags. It is distinguishable from list_languages and get_coverage by subject matter, though the leading verb is implicit (the description leads with the return payload rather than 'lists').

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?

Implies when the data is needed by naming the two downstream parameters it feeds (country_of_use for translation, customer_country for VAT), which is a useful usage hint. However, there is no explicit 'call this before X' instruction and no mention of alternatives or preconditions.

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?

The single annotation stating readOnlyHint: true handles the primary behavioral safety trait. The description adds no unique behavioral information (like rate limits or data constraints) beyond what is implied by the name and the read-only hint.

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?

While short, the structure is highly misleading. It uses its limited space to describe the API usage of sibling functions rather than defining its own function, which is poor definition hygiene.

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?

Despite having zero parameters, the description is not complete because it provides no functional description of the data that will be returned, which is the core expectation for a list tool.

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?

As the tool has zero input parameters, the parameter semantics dimension defaults to high. The description adds no specific clarifying information about the non-existent parameters.

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 is fundamentally flawed as it does not explain what the list_languages tool does. Instead, it discusses parameter acceptance for unrelated sibling tools (get_quote and create_order), making the purpose of this tool completely unclear.

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?

There is absolutely no guidance on when to use list_languages versus any of the other list or creation tools available. The description focuses entirely on external tools, offering zero usage context.

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?

The readOnlyHint annotation already signals a safe read operation, and the description adds useful context about what the returned data includes: units, currencies, quote eligibility, pricing, speeds, certifications, and discount tiers. It does not describe pagination, response format, or any operational constraints, so it adds some value but is not behaviorally rich.

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 definition is a single compact sentence with no filler, and it front-loads the resource being described. The list of returned fields is dense but every clause is relevant, though the lack of an explicit action verb slightly weakens structural clarity.

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?

With no output schema, the description must carry the burden of explaining what the tool returns, and it does so by enumerating services, quote eligibility, prices, currencies, speeds, certifications, discount tiers, and page definitions. It is nearly complete for a no-parameter list tool, though it could more explicitly state that the tool returns all services.

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 the baseline is 4. The description appropriately avoids inventing parameter details, and the rich return-value summary is more relevant than parameter semantics for this no-argument 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 identifies the resource clearly as services sold online and lists the data returned, which lets an agent distinguish this from quote-pricing siblings like get_quote. However, it is written as a noun phrase rather than an explicit verb-resource statement such as 'List services...,' so it stops short of maximum clarity.

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 does not state when to call list_services versus get_quote, list_countries, or other siblings. It mentions get_quote in terms of what data is returned, but gives no explicit usage 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?

The idempotentHint annotation covers repeat-call safety, and the description adds genuinely non-obvious behavior: an email is sent, and the response is deliberately identical whether or not order and email match (anti-enumeration). It does not disclose rate limits, permissions, or whether an email is actually dispatched on a mismatch, but the privacy guarantee is real added value.

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 tight sentences, action front-loaded and the privacy property second. No filler, nothing repeated from the schema.

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?

With no output schema, the description should say what the caller gets back; it only says 'the answer is the same' without describing that answer or whether an email is sent when the match fails. Adequate for calling it, but incomplete on response behavior.

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 both parameters are already documented. The description only lightly reinforces that email must be the address the order was placed with and that it is checked against order_id; the baseline 3 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?

States a specific verb and resource ('Emails the customer fresh pay and status links for an order') with enough specificity to separate it from siblings like get_order_status or send_document. An agent can tell immediately that this is a link-recovery action, not a status read.

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 the trigger (a customer needs their pay/status links again) but never states when to use this versus get_order_status or how to handle a customer who already has the links. No exclusions or alternative paths are named.

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 only openWorldHint in the annotations, the description carries the burden and does so: it discloses the 25 MB size limit, that pages are measured the same way the order form measures an upload (a billing implication), and that the returned file_token is valid for 24 hours and a single order. Those are exactly the non-obvious constraints an agent needs before committing a customer to a paid translation.

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 sentences, each doing distinct work — inputs, downstream contract, fallback — in a sensible order with no filler. The sentences are long and clause-heavy (the first especially), which costs a little readability, but nothing is redundant with the schema or annotations.

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, yet the description still tells the agent what comes back (billable pages and a file_token) plus its lifetime, and it covers the failure path when no input mode is available. For a 4-parameter tool with a nested attachment object, nothing an agent needs to invoke it 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 description coverage is already 100%, so the baseline is 3; the description adds selection semantics beyond the schema by framing the three modes as mutually exclusive choices tied to where the agent holds the file. It does not add format or validation detail beyond what the schema's own field descriptions provide, so it sits just above baseline rather than at the top.

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 opens with a specific verb and resource ('Sends a document to be translated') and immediately enumerates the three accepted input forms with concrete formats (PDF, image or Office file, up to 25 MB). It clearly positions the tool ahead of get_quote/create_order in the workflow by explaining the file_token handoff, so an agent can distinguish it from every sibling without opening a schema.

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 states which input to use in which situation: `document` for chat attachments, `url` for public https links, `content_base64` plus filename 'when you hold the bytes yourself'. It also names an explicit fallback path — create the order from the customer's page count and let them upload at status_url after paying — so the agent knows both when to use this tool and what to do when it cannot be used.

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