massprint

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that no key is issued immediately, the application is reviewed, and the key is emailed to contact_email. It also discloses the invoicing model (GSTIN required, default 25% discount, monthly settlement). While it doesn't cover failure modes or review timelines, it provides substantial 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?

The description is a moderately sized paragraph that front-loads the core purpose and then explains key behaviors and usage restrictions. Every sentence contributes useful context, though it could be slightly more streamlined 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?

The description covers the application flow, requirements, pricing model, and usage guidance. It lacks information about review timelines, rejection reasons, or post-approval steps beyond emailing the key, but given the complexity of an enterprise application and the absence of an output schema, it is reasonably 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 100%, so the baseline is 3. The description adds some context around why GSTIN is required and how contact_email is used, but these are largely restatements of the schema descriptions. It doesn't enrich parameter semantics beyond what the schema already provides.

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+resource ('Apply for an enterprise (invoiced) account') and immediately distinguishes this from order creation by describing the target user: 'platforms printing at volume behind their own checkout.' It also contrasts with sibling tools like create_order by clarifying this is for account setup, not order placement.

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?

Explicitly provides a usage gate: 'Use this only when a human has asked to set up a business/enterprise print account.' It also describes when this tool is appropriate (volume printing, own checkout) and what it does differently from standard order tools (auto-confirm, no payment link, monthly settlement), guiding selection among siblings.

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?

No annotations exist, so the description must disclose behavioral traits. It does so by explaining the status restriction and the manual handling for paid orders. It stops short of describing cancellation effects (e.g., irreversibility, confirmation), but the key behavioral constraint is well covered.

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, front-loaded with the core purpose, followed by condition and alternative. Every sentence earns its place; there is zero 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 simple cancellation tool with two string parameters and no output schema, the description covers the primary context well: what, when, and the alternative. It lacks return-value or failure-mode details, but those are not critical for this tool's simple contract.

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%, and the description does not explain the parameters (order_id, order_token) at all. The names are somewhat self-explanatory, but the description provides no additional context about the token's provenance or format, so it fails to compensate for the lack of schema descriptions.

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 states the tool cancels an order, with a specific verb and resource. It also distinguishes itself from siblings by specifying the condition (awaiting_payment status), which differentiates it from other order-related tools like create_order and get_order.

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?

Explicitly states when the tool is usable (only during awaiting_payment) and provides a clear alternative for paid orders (manual handling, contact support via get_catalog). This gives the agent explicit when-to-use and 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 does so thoroughly. It discloses that validation occurs before payment link minting, the order_token is shown only once, the order auto-confirms after payment, and unpaid orders expire after 72 hours. This significantly exceeds basic expectations.

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 six sentences, all dense with relevant information. It front-loads the core purpose, then efficiently covers return shape, payment URL, token handling, and expiration. No filler or 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?

Despite no output schema, the description fully explains the return object, payment flow, token usage, and expiry behavior. It integrates well with sibling tools by noting that order_token is needed for get_order and cancel_order, providing a complete picture of the order lifecycle.

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 80% (4 of 5 parameters have descriptions), so the schema already documents most parameters. The description adds little parameter-specific detail beyond the precondition of a 'validated upload,' which is not about parameter semantics. Thus, a baseline score of 3 is appropriate.

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 identifies the tool as 'Create a print order for a validated upload,' using a specific verb and resource. It distinguishes itself from siblings like get_order and cancel_order by describing the creation flow and prerequisite (validated upload), making its purpose unambiguous.

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 usage context is clear through references to 'validated upload' as a prerequisite and the note that order_token is required for get_order and cancel_order, implying a sequence. However, it lacks explicit 'when not to use' exclusions, though the context makes alternatives apparent.

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 full burden and exceeds expectations. It discloses the return fields, the need for HTTP PUT with specific Content-Type, that the URL is signed and needs no auth, that the PUT response contains the validation report, and detailed rate limits (20/hour, 5 open, 2-hour expiry). It also advises to reuse upload_id, which is essential 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?

Every sentence adds value: the first states the purpose and return, the second describes the follow-up action, and the third provides critical usage limits and advice. The description is dense but well-structured, with no filler or redundant information. It is front-loaded with the core action.

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 no output schema or annotations, the description fully covers the tool's behavior, return value, next steps, and constraints. It even explains the validation report in the PUT response and how API keys affect limits. This is complete for a tool with this complexity.

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 adds meaningful semantic context about what the tool produces and how to use the result, which compensates for the absence of parameters. It does not describe any parameter constraints because there are none, making the score appropriate.

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: 'Start a PDF upload.' It clearly defines the tool's role as the initial step in the upload workflow, distinguishing it from siblings like create_order (which uses the upload_id) and validate_pdf. The purpose is unambiguous.

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 provides clear workflow context: HTTP PUT to put_url, then pass upload_id to create_order. It also gives practical guidance on rate limits and reusing upload IDs. However, it does not explicitly mention when NOT to use this tool or compare it to alternatives (e.g., validate_pdf), so it stops short of a 5.

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?

No annotations are provided, so the description carries the full burden. It discloses the exact types of information returned (SKUs, formats, sizes, limits, prices, shipping) and implies a read-only listing operation. It doesn't mention response format or error behavior, but for a zero-parameter catalog tool, this is largely sufficient.

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 two sentences, front-loaded with the core purpose ('List what can be printed') followed by a concise enumeration of content and an immediate usage directive. Every sentence earns its place with 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 the tool's simplicity (zero parameters, no output schema), the description is fully complete. It specifies all domains of catalog data and even includes a usage trigger, so an agent can confidently select and invoke this tool without further clarification.

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 and the input schema is empty, so there are no parameter semantics to clarify. The description adds all available meaning about the tool's behavior, meeting the baseline for zero-parameter tools.

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 states the resource (printable items/catalog) and the action (list), enumerating specific content like SKUs, formats, trim sizes, page-count limits, prices, and shipping coverage. It is distinct from sibling tools such as create_order or validate_pdf, which perform different operations.

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 explicit when-to-use guidance: 'Call this first to quote a price or check whether a PDF will be accepted.' This establishes the tool as a prerequisite for pricing and PDF acceptance checks, making the intended usage context unmistakable.

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 burden. It discloses the conditional behavior (payment_url only when unpaid), the status flow, and the prerequisite token. It implies a read-only operation via 'check', but does not explicitly state side effects or error behavior, so a 4 is appropriate.

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 a single, front-loaded sentence that packs essential info (what it returns, conditional logic, prerequisite) without waste. Every clause 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?

Without an output schema, the description should explain return values. It does so by listing status, tracking number, and payment_url. It also covers the prerequisite and conditional behavior. Missing details like error responses are not critical for this simple tool, so a 4 is suitable.

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 input schema already describes order_token, and the description repeats that relationship. The order_id parameter is not described in schema or description, but 'check an order' implies it. The description adds little beyond what the schema provides, especially since schema coverage is 50%. A baseline 3 is fair.

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 states the tool checks an order, with a specific verb 'check' and resource 'order'. It lists the specific fields returned (status, tracking number, payment_url) and distinguishes from sibling tools like create_order and cancel_order by focusing on read-only retrieval.

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 when to use the tool: after creating an order (requires order_token from create_order). It also provides a use case (re-answering 'how do I pay'). However, it does not explicitly state when not to use it or name alternative tools, so it misses the top bar.

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 fully discloses key behavioral traits: it is a read-only report, free, and distinguishes blocking errors (hard) from non-blocking (soft). Also reveals that errors include a resolution field, which is not obvious.

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, front-loaded with purpose, and every clause adds value (contents, blocking nature, cost, usage timing). No redundancy or fluff.

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 single-parameter tool with no output schema, the description is complete: it states what the report contains, the meaning of errors, and when to call it. No critical gaps remain.

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% for the single parameter upload_id, already describing it as returned by create_upload. The description adds no parameter-specific semantics beyond mentioning 'uploaded PDF', so baseline 3 is appropriate.

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 ('Get') and resource ('print-validation report for an uploaded PDF'), and enumerates report contents (page count, trim size, hard errors, soft warnings). Clearly distinct from siblings like create_order or get_order by positioning it as a pre-payment check.

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?

Explicitly says to use it 'before paying' and 'to check printability before create_order', giving clear temporal and contextual guidance. Also notes it is 'Free to call', informing cost/usage decisions.

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