Skip to main content
Glama
Sign In

GadgetHumans API Hub

by com.gadgethumans
OverviewDiscussionsAdmin

ocr

Read every piece of text out of an image and get it back as plain text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "image_url": "<image_url>"
    },
    "name": "ocr"
  }
}

Input Schema

NameRequiredDescriptionDefault
image_urlYesPublic http(s) URL of the image (or pass image=<base64>)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / image_url
      Added value: +{
+  "description": "Public http(s) URL of the image (or pass image=<base64>)",
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "image_url"
+]
  2. Added

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that it extracts text and returns plain text, but omits important details such as supported image formats, limitations (e.g., handwriting, low resolution), error handling, or rate limits, which are critical for an OCR tool.

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 a single, well-structured sentence that front-loads the core action and output with no unnecessary wording. It is appropriately sized for a simple tool.

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

Completeness3/5

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

Given the tool's low complexity (one parameter) and full schema coverage, the description is minimally complete. However, because there are no annotations and no output schema, it could benefit from more behavioral context such as what 'plain text' entails or any constraints, which would help an agent invoke it correctly.

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?

The input schema has 100% description coverage for the single parameter (image_url), including the option to pass base64. The description adds no additional parameter semantics, so the baseline of 3 is appropriate.

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

Purpose4/5

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

The description states a specific verb ('Read') and resource ('every piece of text out of an image') and clearly indicates the output ('plain text'). It does not, however, differentiate this tool from possible siblings like 'caption' or 'extract', which could handle related image or text extraction tasks.

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?

There is no explicit guidance on when to use this tool versus alternatives, nor any mention of prerequisites or exclusions. The description only states what the tool does, leaving the agent to infer the appropriate context.

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

All GadgetHumans API Hub toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources