extract_from_images

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose a meaningful behavioral trait: 'Optional schema steers field names', indicating how the schema parameter affects output. However, it does not mention whether the tool is read-only, how images are handled, or any limitations or side effects, leaving gaps in 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 a single, concise sentence that immediately states the tool's core function and adds relevant examples. There is no wasted wording, and every clause contributes to understanding the tool's purpose and key behavior (schema steering).

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 has 5 parameters, no output schema, and no annotations, the description provides enough context for an agent to understand the primary use case and output type (JSON). The rich schema descriptions fill in parameter details, but the description could more explicitly describe the shape of the return value (e.g., object vs array) and any edge cases. Overall, it is adequately complete but not exhaustive.

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 provides 100% description coverage for all parameters, so the baseline is 3. The description adds a small amount of context by explaining that schema influences field names, but this is already implied in the schema's own description. No additional parameter-level meaning is provided beyond what the schema already covers.

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 uses a specific verb ('Extract') and resource ('images'), and clearly states the output is 'structured data (JSON)'. The enumeration of document types (forms, receipts, IDs, tables, invoices, labels) distinguishes it from sibling tools like describe_image or ocr_image, making the tool's unique 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 clear context for when to use the tool by listing concrete document types (forms, receipts, IDs, tables, invoices, labels). However, it does not explicitly mention when not to use it or name alternative tools for different tasks, such as ocr_image or describe_image, so it stops short of full exclusion guidance.

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