run_apple_ocr

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

With no annotations provided, the description carries the burden. It discloses the OCR engine per platform and approximate speed, but omits potential limitations like image size, format, or language support. The output schema covers return values, but behavioral caveats are missing.

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 sentences long, with the core purpose in the first sentence and platform-specific detail in the second. No extraneous words 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 output schema exists, the description does not need to return values. It covers purpose, parameter, and platform behavior. For a single-parameter tool, it is reasonably complete, though additional context on image constraints would elevate it.

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 only parameter is 'image_base64', and the schema description coverage is 0%. The description adds 'base64-encoded image', which clarifies the string format but adds little beyond the parameter name. No additional constraints (e.g., max size) are given.

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 explicitly states the verb ('Run OCR') and the resource ('base64-encoded image'), making the tool's purpose clear. It also distinguishes from siblings like benchmark and capture_rdp_screen, which are unrelated.

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 platform-specific guidance: on macOS it uses Apple Vision (fast, Neural Engine), on other platforms it uses EasyOCR (with optional GPU). This helps the agent understand performance expectations and installation requirements, though it stops short of explicit when-to-use advice.

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