ocr

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

With no annotations, the description carries the full burden and does well: it discloses formats, the 10 MB limit, that output is text plus a 0-100 confidence score, plus cost ($0.009 USDC/call) and p99 latency (4000ms). It does not mention auth requirements, rate limits, or failure behavior, holding it below 5.

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?

Dense but front-loaded: purpose first, then input constraints, then output, then language, then use cases, then cost/latency. The enumerations are long but each carries actionable information.

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?

There is no output schema, and the description compensates by explaining the return values (text plus confidence with an 80+ reliability threshold), along with cost and latency. For a single-purpose extraction tool this is complete enough to invoke correctly.

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 100%, so the schema already documents all three parameters fully (including psm modes and the full language list). The description largely restates these codes and adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Extract text from images using Tesseract OCR') with the enabling technology named. It is trivially distinguishable from siblings like image_alt_text or pdf_extract.

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?

Gives concrete use cases ('invoices, receipts, scanned documents, or screenshots with text'), which is clear contextual guidance. It stops short of an explicit when-not or routing rule to siblings such as pdf_extract for PDF-native sources, so it does not reach 5.

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