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Save important information to long-term memory with tags, collections, and workspace support. Append to existing memories to prevent duplicates.

Instructions

Save important information to long-term memory. Always set collection when the topic is clear: project work → project:, personal tastes → personal:preferences. Use append_to to extend an existing memory instead of creating duplicates. Vector search indexing completes asynchronously within a few seconds after save. To save to a team workspace instead of personal memory, pass workspace: .

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoOptional tags. A tag like project:my-app also sets collection automatically.
typeNoCategory for this memory. Default: general. Use preference for tastes, fact for stable truths, instruction for rules.general
contentYesThe information to remember.
group_idNoUUID of a shared group. Required with visibility=shared when group_name is not set.
append_toNoUUID of an existing memory to append to (same user). Keeps revision history.
workspaceNoTo operate on a team workspace, pass its exact name, slug, or ID (e.g. "Acme"). Omit — or pass "personal" — for your personal memory (default). Every response echoes resolved_workspace so you can confirm where the operation actually happened. If the user mentions a project or team name in their message, check the memory://workspaces resource (or call list_collections) for the exact matching name BEFORE calling this tool, and pass it as workspace — do not ask the user to spell it out if it already matches one of their workspaces.
collectionNoScope slug (e.g. project:memxus, personal:preferences). GitHub/Notion connector syncs use project:<slug> — one collection per project. Partial names work; call list_collections when unsure.
group_nameNoExact group name (case-insensitive). Alternative to group_id for shared memories.
importanceNoRelevance weight from 0 (low) to 1 (high) for ranking in recall. Default: 0.5.
visibilityNoprivate = personal only (default). shared = save to a group (set group_id or group_name).private

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoTags applied to the memory.
messageYesHuman-readable confirmation (same as content text).
memory_idYesUUID of the saved memory.
collectionNoCollection slug, or empty string if none.
importanceNoStored importance (0–1).
memory_typeYesStored memory category.
resolved_workspaceNoThe workspace this call actually operated on (defense against writing to the wrong team by typo or name collision). id=null means Personal.
Behavior4/5

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

Discloses async vector indexing and echo of resolved workspace. Annotations provide safety hints, but the description adds behavioral context beyond them without contradiction.

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?

Every sentence adds value. Important guidance is front-loaded. No redundant or vague phrasing. Extremely efficient.

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?

Covers purpose, usage, parameters, side effects (async indexing), and confirmation mechanism. With 10 parameters and an output schema, the description is fully self-contained and actionable.

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 coverage is 100%, but the description adds substantial meaning: explains collection naming conventions, workspace resolution process, and usage of append_to. This exceeds the baseline for well-documented schemas.

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 'Save important information to long-term memory', which is a specific verb and resource. It distinguishes itself from sibling tools (list, get) by indicating it is the write operation.

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?

Provides explicit guidance on when to set collection ('project work → project:<slug>'), use append_to (to avoid duplicates), and pass workspace for team saves. Lacks explicit when-not-to-use scenarios, but the instructions are 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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