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Hebbrix

Hebbrix MCP Server

Official
by Hebbrix

hebbrix_search_entities

Search and list entities from a knowledge graph, filtered by type such as people or organizations, for inquiries about known subjects.

Instructions

List entities in the knowledge graph (people, organizations, tools, places), optionally filtered by entity_type. Use for "who/what do I know about" questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
entity_typeNo
collection_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries full burden but only states basic behavior (listing entities, optional filter). It does not disclose pagination, sorting, or whether results are limited (though limit parameter exists). This is adequate for a simple listing tool but leaves some behavioral ambiguity.

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?

Two sentences with no extraneous words. The first sentence states what it does, including examples of entity types, and the second gives a clear usage scenario. Perfectly concise and well-structured.

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?

For a simple listing tool with an output schema (so return format is documented elsewhere), the description covers the essential context: what entities are listed, optional filtering, and typical use case. It could mention pagination behavior but is largely complete.

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 0%, so the description must compensate. It explains the entity_type parameter (filter by type) but does not mention limit or collection_id. While entity_type is the key parameter, the omission of limit and collection_id means the description adds only partial value over 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 tool's purpose: listing entities in a knowledge graph (people, organizations, tools, places) with optional filtering by entity_type, and explicitly ties it to 'who/what do I know about' questions. This directly differentiates it from sibling tools like hebbrix_search or hebbrix_list.

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 provides clear usage guidance ('Use for who/what do I know about questions') but does not explicitly exclude cases where alternatives (e.g., hebbrix_graph_query) would be more appropriate. However, the guidance is sufficient for an agent to decide when to call this tool.

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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