AI eBook Generator

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

With no annotations provided, the description carries the full burden and discloses useful behavioral traits: the URL is temporary, valid for 1 hour, and requires no authentication headers. This adds value beyond the schema, though it does not mention error handling or what happens if the job is not completed.

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 concise sentences with the main purpose stated first, followed by key constraints. There is no redundancy or unnecessary detail, making it highly 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 simple tool with one parameter and no output schema, the description adequately covers the core details: purpose, temporary nature, duration, and authentication requirements. It could be more complete by describing the response format or error scenarios, but the essentials are present.

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 schema already provides 100% coverage for the single parameter, job_id, with the description 'The job ID of the completed book.' The tool description does not add additional parameter semantics beyond what the schema already states, so 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 states the specific action ('Get a temporary signed download URL') and resource ('completed eBook'). This distinguishes it from sibling tools like generate_ebook, get_job_status, list_genres, and retry_job, which have different purposes.

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 this tool should be used for completed eBooks, providing some context, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. No guidance on checking job status first or using retry_job if needed.

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 of behavioral disclosure. It transparently reveals costs ($0.90/chapter), the requirement to pay via a returned link before generation begins, and the need to switch to get_job_status afterward. This is critical context for a paid service, though it doesn't detail failure modes or response format.

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 that are front-loaded with the primary action, then cost, then payment flow. Each sentence earns its place with no fluff 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?

Although there is no output schema, the description provides the essential behavioral information: it initiates generation, returns a payment link, requires payment before proceeding, and points to get_job_status for tracking. This is complete enough for an agent to use the tool correctly in the given workflow, though it doesn't specify the full response structure.

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 covers all 9 parameters with descriptions, so baseline is 3. The description adds no parameter-specific meaning beyond the cost-per-chapter implication tied to chapter_count, which is not explicitly linked to the parameter.

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?

Clear verb 'generate' + resource 'eBook' with explicit statement that it starts multi-chapter generation and returns a payment link. Fully distinguishes from siblings like get_job_status, which tracks progress.

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 directs the user to use get_job_status after payment, establishing a clear workflow for this tool versus the sibling tracking tool. It doesn't explicitly state when not to use it, but the payment-gated flow implies it's for initiation only.

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 of behavioral disclosure. It clearly states the return fields (status, chapters_done, total_chapters) and the conditional nature of download_url (only when complete), which gives the agent insight into expected behavior. It stops short of describing error cases or eventual statuses like failure, but for a status-check tool it provides adequate 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?

The description is two concise sentences. The first sentence states the action and target, and the second lists the return values and their condition. There is no wasted wording or redundancy, making it efficient and easy to parse.

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 lack of an output schema and annotations, the description does well by explicitly listing return fields and the condition for download_url. However, it does not mention possible job statuses (e.g., failed, pending) or how to handle errors, which could be inferred from the sibling retry_job tool. For a simple polling tool, this is nearly complete but leaves a small gap around failure handling.

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 provides 100% coverage for the single parameter job_id with a clear description ('The job ID returned by generate_ebook'). The tool description does not add any additional meaning or constraints about the parameter, so it does not exceed the baseline set by schema coverage.

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 action ('Check the status and progress') on a clear resource ('an eBook generation job'). It distinguishes this tool from siblings like generate_ebook, retry_job, and download_epub_url by focusing on status retrieval. The purpose is unambiguous and directly actionable.

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 usage after job creation (via 'download_url when complete' and the schema's reference to generate_ebook), but it does not explicitly state when to use this tool versus alternatives like retry_job. No exclusions or alternative conditions are provided, so the guidance is limited to an implied workflow rather than explicit recommendations.

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 implies a read-only operation via the word 'List' and adds sequencing context, but it does not explicitly disclose side effects, return format, or any operational traits beyond that. For a simple list tool, this is adequate but not 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?

Two sentences, no redundancy. The first sentence states the function, the second provides usage guidance. Every word earns its place, and the information is front-loaded.

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 tells the agent what the tool returns (genres and themes) and when to call it. Since there is no output schema, it does not detail the return structure, but for a simple list tool with no parameters, this is sufficient for an agent to select and invoke 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?

The tool has zero parameters, so the baseline is 4. The description correctly focuses on the output and usage rather than parameter semantics, which are irrelevant here.

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 action ('List all available genres and their themes'), the resource (genres/content types), and the context (for eBook generation). It also distinguishes this from sibling tools by positioning it as a discovery step before generation.

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 explicitly says 'Call this first,' providing clear when-to-use guidance. It does not explicitly mention when not to use it or name alternatives, which would merit a 5, but the sequencing advice is valuable and unambiguous.

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 burden of behavioral disclosure. It reveals two key behaviors: the operation does not charge again, and it re-queues the original job. This goes beyond a generic retry claim, though it doesn't cover potential side effects or return values.

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 with no fluff. The first sentence states the action and target; the second clarifies the usage context and alternative. Front-loaded and 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 simple retry tool with a single parameter and no output schema, the description is complete: it covers purpose, usage triggers, and differentiation from alternatives. No missing information that would hinder correct selection or invocation.

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 parameter job_id is fully documented in the schema. The description adds no additional parameter semantics beyond restating that it is the previously paid job, which is already in the schema description. 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 clearly states the tool's function: 'Retry a paid eBook generation job that failed server-side.' It explicitly distinguishes from sibling tool generate_ebook, which creates a new payment, making 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 description provides explicit when-to-use guidance: 'use this whenever get_job_status reports a failed job that was previously paid for.' It also names the alternative (generate_ebook) and explains why not to use it (would create a new payment), offering clear exclusions.

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