extract_image_text

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

With no annotations, the description carries the behavioral burden; it clearly states reading-order OCR behavior and that the input must be a local image file. It doesn't dwell on side effects, but 'Extract' signals a non-mutating read operation, and output details are handle by the output schema.

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 a clear purpose, followed by a concise workflow and an Args block. Every sentence adds useful information and there is no filler.

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?

This is a single-parameter OCR tool with an existing output schema; the description covers what it does, when to use it, and the only parameter's constraints. Nothing essential is missing for correct 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 description coverage is 0%, but the Args block fully documents image_path, adding local-path semantics and supported formats (PNG, JPEG, WebP) that the schema alone lacks.

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 and resource: 'Extract text segments from an image, in reading order (OCR).' It also distinguishes itself from sibling localize_image by positioning extraction as the first step before re-rendering.

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 explicitly says when to use the tool: 'Use this as the first step when localizing an image,' and gives the full workflow with translate and localize_image. It doesn't state a when-not or compare to parse_subtitle, so it falls just 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.