extract_text_umi_v2

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: automatic paragraph merging, confidence filtering, token saving, and handwriting model switching. This provides sufficient transparency for a read-only tool without destructive side effects.

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 concise (three lines for purpose, two for bullet features, two for params) with clear structure and no redundant text. Every sentence adds value, making it easy for an AI agent to parse 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 simplicity (2 parameters, output schema present), the description covers the core functionality and parameter guidance. It lacks return format details, but the output schema fills that gap. Overall, it is sufficiently complete for standard use.

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 has 0% description coverage, so the description must compensate. It meaningfully explains both parameters: file_path as 'absolute local path' and is_handwritten as 'switch handwriting model', adding context beyond the schema fields. This is adequate for the two parameters.

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 tool extracts text from local images using Umi-OCR v2.1.5, with specific features like paragraph merging and confidence filtering. It distinguishes from sibling tools (e.g., ocr_batch, ocr_directory) that handle different inputs or batch processing, making the 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 specifies the tool is optimized for AI reading and automatically processes paragraphs, implying its use for single-image text extraction with built-in preprocessing. However, it does not explicitly state when not to use it or suggest alternatives, though sibling names provide implicit guidance.

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