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extract_entities_bulk

Process multiple documents in a batch to extract named entities. Skip documents with existing entities unless force regeneration is enabled, and return statistics on processed documents and extracted entities.

Instructions

Bulk extract entities from multiple documents in the knowledge base. Processes documents in batch, skips documents that already have entities (unless force_regenerate). Returns statistics about processed documents and extracted entities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confidence_thresholdNoMinimum confidence to include entity (0.0-1.0, default: 0.6)
force_regenerateNoForce re-extraction even if entities already exist (default: false)
max_docsNoMaximum number of documents to process (optional, for testing)
skip_existingNoSkip documents that already have entities (default: true)
Behavior3/5

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

With no annotations, the description carries the burden. It states batch processing and skipping behavior, which are useful, but does not disclose whether entities are persisted, any destructive actions, or rate limits. The description is adequate but leaves some behavioral aspects implicit.

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 sentences, front-loaded with purpose, and contains no redundant information. Every sentence earns its place.

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 4 parameters (all described in schema) and no output schema, the description covers the overall behavior (batch processing, skipping logic) and return type (statistics). It is complete enough for an agent to understand the tool's function, though specific statistics format is not detailed.

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%, so the description adds limited value beyond the schema. It reinforces the skip existing and force regenerate logic but does not provide additional parameter context beyond what is already in the schema.

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 clearly states the verb 'extract' and resource 'entities from multiple documents', distinguishing it from single-document extraction tools like 'extract_entities' by emphasizing 'bulk' and 'batch'.

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 explains that it processes documents in batch and skips documents with existing entities unless force_regenerate is set, providing good context. However, it does not explicitly compare with siblings like 'extract_entities' or 'queue_entity_extraction' for when to choose this tool over alternatives.

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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