Skip to main content
Glama

memory_forget

Permanently forget a capsule's content with a mandatory reason. Purged mode erases everything; redacted mode retains provenance for audit—both irreversibly destroy data.

Instructions

Forget a capsule's content IRREVERSIBLY (reason MANDATORY). The capsule's embedding sidecar row is destroyed WITH it (both modes — a vector is derived from the destroyed bytes and the id stops being enumerable on memory_vector's list). mode "purged" = hard forget, nothing retained; "redacted" = the provenance {source, anchor} is deliberately RETAINED on the marker for audit — both destroy the content bytes (secure_delete) and empty the recall index row. What remains is the tombstone marker: id, mode, at, reason, a KEYED HMAC-SHA-256 content fingerprint (key from NMEMORY_HMAC_KEY or a 0600 key file beside the DB, created on first use), the id's relation edges, and — redacted only — the retained provenance. Afterwards: memory_get answers the marker envelope (memory_list omits tombstoned ids); retrieve counts it under excluded {tombstoned} ONLY when a query term IS the capsule id itself (e.g. terms:["cap-3"]); the content index row is EMPTIED, so searching the forgotten content abstains — zero matches, no tombstone echo; re-ingesting the identical content is rejected (forget is sticky); the id drops out of the digest dag (forget is a sanctioned dag repair); forgetting the id AGAIN is a resource-state error (-32002, data {kind: "tombstoned_capsule", id}) — the same family as an unknown id, never a fake invalid-params. Audited with the reason.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe capsule to forget (`cap-<n>`).
modeYesHow: `purged` (hard forget) or `redacted` (provenance retained for audit). Both destroy the content bytes.
reasonYesThe mandatory stated reason (recorded on the marker + audit).
Behavior5/5

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 extensively details behavioral traits: secure delete, tombstone marker, HMAC fingerprint, effect on memory_get/memory_list/retrieve, re-ingestion rejection, dag repair, and error codes. This is comprehensive.

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

Conciseness3/5

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

The description is very detailed but quite lengthy and dense as a single paragraph. While thoroughness is justified for a destructive operation, it could be more structured (e.g., using bullet points) to improve readability for an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of this irreversible operation with two modes and side effects on multiple subsystems, and no output schema, the description is highly complete. It covers all important behavioral aspects and error conditions.

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?

Schema coverage is 100%, so baseline is 3. The description adds value beyond the schema by explaining the purpose of each parameter and elaborating on the mode parameter's consequences (e.g., 'Both destroy the content bytes'). This extra context justifies a score above baseline.

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's purpose: 'Forget a capsule's content IRREVERSIBLY' with a mandatory reason. It distinguishes from sibling tools like memory_get (retrieve) and memory_ingest (create) by specifying irreversible deletion.

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 provides clear context on when to use this tool (irreversible deletion) and explains the two modes (purged vs redacted) with their implications. It also mentions when re-ingestion is rejected and that forgetting again produces an error, but does not explicitly name alternative tools for non-destructive operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/menot-you/n-memory'

If you have feedback or need assistance with the MCP directory API, please join our Discord server