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ocr_url

Extract text from a publicly accessible image or PDF using OCR.space API. Convert scanned documents into editable text.

Instructions

Extract text from an image or PDF at a URL using OCR.space API. The URL must be publicly accessible. Free tier: max 1 MB. PRO tier: max 5 MB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic URL of the image or PDF to OCR
tierNoAPI tier: 'free' (1MB limit, US servers) or 'pro' (5MB limit, EU/GDPR)free
scaleNoUpscale low-resolution images
is_tableNoOptimize for tables
languageNoOCR language code (e.g., 'eng', 'ger', 'fre'). Use 'auto' with Engine 2.eng
ocr_engineNoEngine 1: Faster, Asian languages. Engine 2: Auto-detect, better accuracy.
output_pathNoOptional path to save extracted text (.txt) or full result (.json)
output_formatNoOutput format: 'txt' (text only) or 'json' (full API response)txt
detect_orientationNoAuto-rotate image
Behavior3/5

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

No annotations are provided, so the description carries the full transparency burden. It discloses that the tool uses an external API, requires public URL access, and has size limits based on tier. However, it does not mention output behavior, potential network/security implications, or what happens on failure. It adds some value but lacks richer behavioral disclosure.

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 three sentences long, front-loaded with the main purpose, and each sentence adds meaningful information (action, URL requirement, size limits). No wasted words, and the structure is easy to scan.

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 has 9 parameters, no output schema, and no annotations, the description provides essential context: what it does, the external API dependency, and key constraints. The schema covers the remaining parameter details. It is reasonably complete for the tool's complexity, though it could mention error/edge cases or further usage context.

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 description coverage is 100% (all 9 parameters have descriptions in the schema), so the baseline is 3. The tool description does not add additional parameter meaning beyond what the schema already provides; the schema thoroughly documents each parameter, so more detail in the description is unnecessary.

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 begins with 'Extract text from an image or PDF at a URL', which clearly specifies the action (extract text), the resource (image/PDF at a URL), and distinguishes it from the sibling tool ocr_file (which likely handles local files). It also names the underlying API (OCR.space) for additional context.

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

Usage Guidelines4/5

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

The description clearly indicates the tool is for URLs by stating the URL must be publicly accessible and provides size limits for free vs PRO tiers. This gives clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions compared to sibling tools like ocr_file or ocr_auto.

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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