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originality_batch_scan

Process multiple content items in one request with uniform scan options for AI detection, plagiarism, fact-checking, readability, grammar, and SEO optimization.

Instructions

Process multiple content scans in a single request. Each item uses the same scan options. More efficient than individual scans for bulk content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesArray of content items to scan
check_aiYesEnable AI detection for all items
check_plagiarismYesEnable plagiarism detection for all items
check_factsYesEnable fact checking for all items
check_readabilityYesEnable readability analysis for all items
check_grammarYesEnable grammar checking for all items
check_contentOptimizerYesEnable SEO optimization for all items
aiModelVersionYesAI detection model to use
storeScanNoWhether to persist results for later retrieval
Behavior2/5

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

No annotations are provided; description merely mentions 'same scan options' and efficiency, but omits critical behavioral details like batch size limits, credit consumption, error handling, and result ordering.

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?

Extremely concise: two sentences that front-load purpose and efficiency benefit. No superfluous information.

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

Completeness2/5

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

No output schema; description fails to explain return values, error handling, or how to interpret batch results. Lacks credit cost or rate limit context essential for a batch operation.

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% with clear descriptions. The tool description adds minimal extra meaning beyond stating that options apply uniformly across items, which is already implied.

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?

Description clearly states the verb 'process' and resource 'multiple content scans'. It distinguishes from siblings by explicitly noting efficiency for bulk content compared to individual scans.

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?

Description implies usage for bulk scanning with efficiency benefit, but lacks explicit exclusion criteria or comparison with sibling tools like originality_scan for different options per item.

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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