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forget

Delete specific knowledge from the graph by removing entities, relations, sessions, or entire datasets to correct or clear memory.

Instructions

Forget an entity (and its relations) by exact name, a relation by id, a session, or a whole dataset. Prefer supersede for facts that were true once. Confirm with the user first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityNo
datasetNo
session_idNo
relation_idNo
whole_datasetNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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 discloses destructive scope by saying an entity is forgotten 'and its relations' and specifies exact-name matching. It also signals that the operation is sensitive by requiring user confirmation, though it stops short of explicitly stating permanence or irreversibility.

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 three short sentences with no filler. The main action is front-loaded, and the alternative tool and user-confirmation requirement each earn their place.

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?

Given five optional parameters, no annotations, and no output schema, the description is reasonably complete for the core action but leaves the 'dataset' parameter ambiguous. It also does not state what happens when multiple parameters are provided or what a successful 'forget' returns, so an agent may lack enough context to call it confidently in all cases.

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 0%, so the description must compensate for the undocumented parameters. It explains entity, relation_id, session_id, and whole_dataset in natural language and adds exact-match semantics. However, the 'dataset' parameter is never explained, and the relationship between 'dataset' and 'whole_dataset' remains ambiguous.

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 states a specific verb ('Forget') with concrete targets: an entity by exact name, its relations, a relation by id, a session, or a whole dataset. It also differentiates from the sibling tool 'supersede' by saying to prefer supersede for facts that were once true, which prevents conflation with a similar memory-editing tool.

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

Usage Guidelines5/5

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

The description explicitly tells the agent when not to use this tool ('Prefer supersede for facts that were true once'), naming the alternative. It also gives a clear prerequisite: 'Confirm with the user first.' This is sufficient usage guidance for a destructive memory operation.

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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