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yamantaka520

agent-memory-os

by yamantaka520
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

memory_link

Create directed associations between memories to reinforce recall, connecting decisions to causes or fixes to problems.

Instructions

Create a directed association between two existing memories.

    Linked memories reinforce each other in recall, so a search that hits one can
    surface the other even with no shared keywords. Use it to connect a decision to
    its cause, or a fix to the problem it solved. Returns the created link, or an
    `{"error": ...}` object if either memory id does not exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dst_idYesId of the destination memory to associate with the source.
src_idYesId of the source memory (from memory_add/memory_search).
weightNoAssociation strength from 0.0 to 1.0; higher means the memories surface together more strongly.
relationNoRelationship type: 'related_to', 'supersedes', 'caused_by', 'derived_from', or 'co_recalled'.related_to

Tool Definition Quality

A4/5.0
Behavior3/5

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

No annotations are provided, so description carries full burden. It discloses that linked memories reinforce recall and returns either a created link or an error. However, it omits side effects like reversibility, authorization needs, or impact on existing links.

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 four sentences, front-loaded with the main purpose, and no wasted words. It efficiently communicates purpose, behavioral impact, and return value.

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 no output schema, the description adequately mentions return type ('created link or error'). With 4 parameters, it covers the essential behavior, though lacks details on how weight affects recall in practice. Still fairly complete for a simple tool.

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%, so baseline is 3. The description adds minimal semantic value beyond schema: it mentions linking decisions and fixes but does not elaborate on weight or relation behavior beyond what schema already states.

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 a directed association between two existing memories' with specific verb and resource. It distinguishes from siblings like memory_add (creates new memories) by focusing on linking existing ones.

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 gives explicit use cases: 'connect a decision to its cause, or a fix to the problem it solved.' It doesn't provide explicit negative guidance or alternatives, but the use cases are clear enough given the sibling set.

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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