extract_region

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

With no annotations, description carries full burden. It discloses a key behavioral trait: region is cropped before being sent to the vision provider, saving tokens and producing focused results. No mention of mutability or auth, but appropriate for a read-only analysis tool.

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?

Five sentences, front-loaded with action, each sentence adds unique value: purpose, usage examples, parameter specification, benefits. 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?

Given the complexity (6 parameters including nested object and enums) and the presence of an output schema, the description provides high-level context and region parameter details, but omits explanation of mode, prompt, image_url, and image_path. Could be more complete for parameter-rich 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 coverage is 0% (no parameter descriptions in schema). The description adds meaning for the region parameter (pixel coordinates), but does not explain mode, prompt, detail_level, image_url, or image_path. It partially compensates by giving usage examples that hint at mode, but insufficient for full guidance.

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?

Description clearly states the verb-resource (extract and analyze a specific region), and gives concrete examples (error popup, chart, UI component) that distinguish it from sibling tools like analyze_image, which likely handle full images.

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 'Use this when a coding agent needs to focus on a particular area' and lists specific scenarios. Implicitly advises against using for full-image analysis, effectively 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.