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memory_relate

Create directional links between memories to build a knowledge graph. Related memories surface automatically during recall, providing connected context.

Instructions

Create a directional link between two memories. Relations are used by spreading activation (recalling one memory wakes its related cluster) and are returned when include_related=True in memory_recall. Use to build a knowledge graph that surfaces connected context automatically.

source_id is the memory making the claim about target_id. relation_type must be one of: supersedes (source replaces target), related_to (general connection), caused_by (source was caused by target), contradicts (conflicting claims), parent_of (source contains target), child_of (source belongs to target).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_idYes
target_idYes
relation_typeYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that relations affect spreading activation and are returned in recall with include_related=True, and explains directionality. However, it does not mention side effects, error cases, or idempotency, which is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and uses clear structure. It is somewhat dense but efficient, providing necessary details without extraneous content. Could be slightly more streamlined, but earns its sentences.

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 three parameters, no output schema, and no annotations, the description covers the essential purpose, directionality, relation types, and integration with recall. Minor gaps exist (e.g., error handling for invalid relation_type or missing memories), but completeness is strong overall.

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

Parameters5/5

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

Schema description coverage is 0%, so the description compensates fully. It explains that source_id is the memory making the claim, target_id is the memory being claimed about, and lists all valid relation_type values with their meanings, adding critical semantic detail absent from 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 creates a directional link between two memories, a specific verb+resource combination. It distinguishes from sibling tools like memory_recall and memory_store by explaining that relations are used for spreading activation and returning related memories.

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 when to use the tool (to build a knowledge graph for automated context) and provides detailed guidance on source/target directionality and relation types. It lacks explicit exclusions or mention of alternatives, but the context is sufficiently clear.

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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