memxus

Remember

remember

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

Name	Required	Description	Default
`tags`	No	Optional tags. A tag like project:my-app also sets collection automatically.
`type`	No	Category for this memory. Default: general. Use preference for tastes, fact for stable truths, instruction for rules.	general
`content`	Yes	The information to remember.
`group_id`	No	UUID of a shared group. Required with visibility=shared when group_name is not set.
`append_to`	No	UUID of an existing memory to append to (same user). Keeps revision history.
`workspace`	No	To 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. Call list_collections when unsure of the exact workspace name.
`collection`	No	Scope 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_name`	No	Exact group name (case-insensitive). Alternative to group_id for shared memories.
`importance`	No	Relevance weight from 0 (low) to 1 (high) for ranking in recall. Default: 0.5.
`visibility`	No	private = personal only (default). shared = save to a group (set group_id or group_name).	private

Output Schema

TableJSON Schema

Name	Required	Description
`tags`	No	Tags applied to the memory.
`message`	Yes	Human-readable confirmation (same as content text).
`memory_id`	Yes	UUID of the saved memory.
`collection`	No	Collection slug, or empty string if none.
`importance`	No	Stored importance (0–1).
`memory_type`	Yes	Stored memory category.
`resolved_workspace`	No	The workspace this call actually operated on (defense against writing to the wrong team by typo or name collision). id=null means Personal.

TDQS

A4.2/5.0

Behavior4/5

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

Discloses that 'Vector search indexing completes asynchronously within a few seconds after save' and that append_to 'Keeps revision history,' adding value beyond annotations. Annotations already indicate readOnlyHint=false and destructiveHint=false, so the description complements them well.

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

Conciseness4/5

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

The description is a single paragraph that front-loads the purpose and then provides guidelines. It is efficient given the number of parameters (10), with no wasted sentences.

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?

With an output schema present and the description covering purpose, usage, and behavior, it is largely complete. It could mention typical return values (e.g., memory ID) but the output schema likely handles that.

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 extra meaning such as 'Partial names work; call list_collections when unsure' for collection, and 'Every response echoes resolved_workspace so you can confirm' for workspace, improving usability.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 specific and uses a verb+resource. It adds context about collections and append_to, but does not explicitly differentiate from sibling tools like recall or list_memories.

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?

Provides explicit guidance: 'Always set collection when the topic is clear,' 'Use append_to to extend an existing memory instead of creating duplicates,' and 'To save to a team workspace instead of personal memory, pass workspace: <name>.' It also advises calling list_collections when unsure, covering both when-to and alternatives.

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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TDQS

A4.4/5.0

Disambiguation5/5

Each tool has a clear, distinct purpose: forget deletes, remember saves, update modifies, recall searches, list_memories lists, get_memory retrieves full details, get_context builds a context block, list_collections lists folders, memory_stats shows counts. There is no functional overlap that would confuse an agent.

Naming Consistency3/5

Names mix conventions: forget, recall, remember, update are single verbs; get_context, get_memory, list_collections, list_memories follow verb_noun; memory_stats is noun_noun. This inconsistency can make it harder for an agent to predict tool names.

Tool Count5/5

With 9 tools, the server is well-scoped for a memory management system. Each tool addresses a core operation (CRUD, search, stats, context building) without unnecessary redundancy. The count is appropriate for the domain.

Completeness4/5

The surface covers create (remember), read (list_memories, get_memory, recall, get_context), update (update), delete (forget), plus metadata tools (list_collections, memory_stats). Missing explicit filtering by tags or bulk operations, but these are minor gaps given the semantic search capability.

Remember

Input Schema

Output Schema

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