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jmars

memory-mcp

by jmars

create_entities

Batch-create entities in the knowledge graph, each with a name, entity type, and observations.

Instructions

Create multiple new entities in the knowledge graph.

Each entity must have: name (str), entityType (str), observations (list[str]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entitiesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only lists required fields but does not disclose behaviors such as idempotency, error handling, duplicate handling, or return format. This is a significant gap for a mutation tool with no annotation support.

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: the first states the purpose, the second enumerates required fields. It is concise, front-loaded, and every sentence contributes meaning without wasted words.

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?

The tool is simple with one parameter, and an output schema exists, so return values need no explanation. However, the description lacks usage guidance and behavioral context, and with no annotations, the agent is left with incomplete information about side effects or failure modes. This is adequate but has clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema shows only a single 'entities' array with no property descriptions (coverage 0%). The description compensates by explicitly specifying the required fields (name, entityType, observations) and their types, providing essential meaning beyond the schema's permissive additionalProperties.

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 'Create multiple new entities' with a specific verb and resource, and the context of a knowledge graph distinguishes it from siblings like create_relations and add_observations. It unambiguously communicates what the tool does.

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

Usage Guidelines3/5

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

The usage context is implied by the tool name and the sibling tools (e.g., creating entities vs. relations/observations), but the description does not explicitly state when to use this tool over alternatives or any exclusions. It gives no direct 'when-to-use' guidance beyond the basic action.

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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