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by com.mart402
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Ocr Image

ocr_image
Idempotent

OCR one image to text with dual-engine consensus, calibrated confidence and per-segment corroboration. Japanese-strong. Flat $0.05/image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoOne of: japanese, latin. Expected script for OCR: japanese or latinjapanese
image_urlNoAbsolute http(s) URL of the image (JPEG/PNG/WebP)
x_paymentNoOptional: base64 X-PAYMENT header value (x402 exact scheme, USDC on Base mainnet). Omit it to receive the payment requirements (accepts[] + docs) for this call without being charged.
image_base64NoBase64-encoded image bytes (alternative to image_url)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / lang / description
      Previous value: -"Expected script for OCR: japanese or latin"New value: +"One of: japanese, latin. Expected script for OCR: japanese or latin"
  2. Changed3 schema fields changed
    • addedInput schema / properties / image_base64 / description
      Added value: +"Base64-encoded image bytes (alternative to image_url)"
    • addedInput schema / properties / image_url / description
      Added value: +"Absolute http(s) URL of the image (JPEG/PNG/WebP)"
    • addedInput schema / properties / lang / description
      Added value: +"Expected script for OCR: japanese or latin"
  3. Changed2 schema fields changed
    • addedInput schema / properties / x_payment
      Added value: +{
+  "description": "Optional: base64 X-PAYMENT header value (x402 exact scheme, USDC on Base mainnet). Omit it to receive the payment requirements (accepts[] + docs) for this call without being charged.",
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[]
  4. Added

TDQS

A3.6/5.0
Behavior3/5

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

The description adds behavioral context beyond annotations by disclosing the flat fee ($0.05/image) and the dual-engine/calibration process, which annotations do not cover. However, readOnlyHint: false implies possible side effects, and the description does not clarify what those are beyond charging, nor does it mention any limitations or prerequisites.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences that front-load the core purpose ('OCR one image to text') and then pack additional differentiators and pricing efficiently. There is zero wasted verbiage; every clause adds information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (4 parameters, none required, no output schema), the description combined with the schema provides sufficient information for an agent to call it correctly: how to specify the image (url or base64), language, and the payment mechanism. It lacks explicit error or rate-limit info, but that is not critical for a simple call. The pricing and process details fill gaps not covered by annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for all 4 parameters, so the baseline is 3. The description adds context about language strength (Japanese-strong) and pricing, but does not add any parameter-specific semantic details beyond what the schema already provides. It does not explain the relationship between image_url and image_base64 beyond what the schema states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('OCR one image to text') with a clear resource, and adds unique differentiators (dual-engine consensus, calibrated confidence, per-segment corroboration) that distinguish it from general document tools like document_pipeline or parse_document. The focus on a single image makes the scope unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is given on when to use this tool over alternatives. The phrase 'Japanese-strong' implies suitability for Japanese text but does not explicitly say 'use this for Japanese images' or mention any exclusions or sibling comparisons. An agent would have to infer usage context.

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

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