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 does so effectively. It discloses key behavioral traits: the URL is temporary (valid for 1 hour), signed, and doesn't require authentication headers. This gives the agent crucial information about the tool's operation and constraints.

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 perfectly concise with two sentences that each earn their place. The first sentence states the core purpose, and the second adds essential behavioral details. There's zero waste 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?

For a single-parameter tool with no annotations and no output schema, the description is quite complete. It explains what the tool returns (a temporary signed URL) and key constraints. The main gap is not explicitly mentioning the output format or error conditions, but it's sufficient for the tool's 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?

Schema description coverage is 100%, so the schema already documents the job_id parameter. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or relationship to sibling tools. Baseline 3 is appropriate when schema does the heavy lifting.

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 ('for a completed eBook'), distinguishing it from sibling tools like generate_ebook (creation) and get_job_status (status check). It precisely defines what the tool does beyond just the name.

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 context for when to use it ('for a completed eBook'), implying it should be used after a book is ready. However, it doesn't explicitly state when NOT to use it or name alternatives like get_job_status for checking completion status first.

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 effectively describes key behavioral traits: the cost structure ($0.45 per chapter), the payment workflow (returns a payment link, user must pay before generation), and the asynchronous nature (track progress with get_job_status). However, it doesn't mention potential rate limits, error conditions, or time estimates for generation.

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 appropriately sized and front-loaded, with three sentences that each earn their place: the first states the core action, the second explains costs and payment, and the third provides workflow guidance. There's zero waste 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?

Given the complexity (a paid, asynchronous AI generation tool with 9 parameters) and no annotations or output schema, the description does a good job covering the essential context: purpose, cost, payment workflow, and next steps. However, it lacks details on output format (e.g., what get_job_status returns) and error handling, which would be helpful for full completeness.

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 description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how parameters like 'tone' or 'genre' affect generation. This meets the baseline of 3 when schema coverage is high.

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 ('Start generating a complete multi-chapter eBook using AI'), identifies the resource (eBook), and distinguishes it from siblings by mentioning the payment workflow and referencing get_job_status for tracking. It goes beyond just restating the name to explain the full process.

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 states when to use this tool ('Start generating...') and when to use an alternative ('use get_job_status to track progress'), providing clear guidance on the workflow. It also mentions prerequisites (payment required) and distinguishes it from download_epub_url and list_genres by focusing on the generation initiation.

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. It discloses the return values (status, chapters_done, total_chapters, download_url) which is helpful behavioral context. However, it doesn't mention error conditions, rate limits, authentication needs, or whether this is a read-only operation (though implied by 'check'). It adds value but lacks comprehensive behavioral details.

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, well-structured sentence that efficiently conveys purpose, usage context, and return values. Every word earns its place with zero waste, making it easy to parse and understand quickly.

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 low complexity (one parameter, no output schema), the description is reasonably complete. It explains what the tool does, when to use it, and what it returns. However, without annotations or output schema, it could benefit from more behavioral details (e.g., error handling), but it covers the essentials adequately for this simple 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?

Schema description coverage is 100%, with the job_id parameter fully documented in the schema. The description adds minimal value beyond the schema by mentioning job_id comes from generate_ebook, but doesn't provide additional syntax, format, or constraints. This meets the baseline of 3 when schema coverage is high.

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 ('check the status and progress') and resource ('eBook generation job'), distinguishing it from siblings like generate_ebook (which creates jobs) and download_epub_url (which downloads results). It precisely defines what the tool does without being vague or tautological.

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 implicitly indicates when to use this tool: after generating an eBook job to monitor its progress. It mentions the job_id parameter comes from generate_ebook, providing context. However, it doesn't explicitly state when NOT to use it or name alternatives (e.g., if you need to list jobs, though no such sibling exists), so it falls short of a perfect 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?

With no annotations provided, the description carries the full burden. It describes the tool's purpose (listing genres/themes for discovery) but doesn't disclose behavioral traits like rate limits, authentication requirements, or response format details. The description doesn't contradict annotations (none exist), but provides only basic operational 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 perfectly concise with two sentences that each earn their place: the first states what the tool does, the second provides critical usage guidance. It's front-loaded with the core purpose and wastes no 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?

For a zero-parameter discovery tool with no annotations or output schema, the description provides sufficient context about what information will be returned (genres and their themes) and its role in the workflow. It could be slightly more complete by mentioning the response format, but given the tool's simplicity, it's largely adequate.

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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the tool's purpose and usage context.

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 verb ('List') and resource ('all available genres (content types) and their themes for eBook generation'), distinguishing it from sibling tools like generate_ebook (which creates books) and download_epub_url/get_job_status (which handle outputs/status). It explicitly mentions the tool's role in discovering what Scrivibe can create.

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 guidance on when to use this tool ('Call this first to discover what types of books Scrivibe can create'), positioning it as an initial discovery step before using sibling tools like generate_ebook. It clearly differentiates this from other tools that perform generation, download, or status checking operations.

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