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brain_forget

DestructiveIdempotent

Remove outdated or irrelevant memories by ID, file path, or search query. Deprecate to preserve audit history, or permanently purge with hard delete.

Instructions

Remove or deprecate specific memories from Local Brain. Can target a memory by ID, file path, or search query. By default deprecates the memory to maintain audit trail; pass hard_delete: true to purge.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoExact memory ID to forget.
queryNoForget memories matching this text/topic.
file_pathNoForget all memories associated with this file path.
hard_deleteNoIf true, permanently deletes records from SQLite. Default is false (marks deprecated).

Schema Changelog

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

  1. First observedv1.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the annotations (destructiveHint=true, idempotentHint=true), the description clearly discloses the soft-delete default, the audit-trail rationale, and the hard_delete behavior that purges records. It adds meaningful context about what happens to the data without contradicting the annotations.

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 dense sentences with no filler. The core action and targeting options come first, followed by the destructive/soft-delete distinction that matters most for a destructive tool.

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 description covers the main action, selectors, and default vs purge behavior, and the annotations cover safety. It is still missing guidance on whether at least one target selector is required, whether selectors are mutually exclusive, and what the tool returns or reports after forgetting.

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 the schema already documents id, query, file_path, and hard_delete. The description usefully recasts them as targeting strategies and explains the default behavior of hard_delete, but it does not add details beyond what the schema provides, so the baseline of 3 is appropriate.

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 opens with a specific verb phrase ('Remove or deprecate specific memories') and a clear resource ('Local Brain'), then names three targeting modes (ID, file path, search query). This makes it distinct from its sibling retrieval and pruning tools even though no sibling is named.

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 intended use is implied: call this when you need to forget memories, choosing an ID, file path, or query. However, it does not explicitly contrast with tools like brain_prune or brain_learn, and it does not state whether one selector is required or how to choose among the three when several apply.

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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