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Remember in XMemo

remember

Save durable facts, preferences, and instructions for automatic recall in future conversations.

Instructions

Save a memory so it can be recalled in future conversations. Call this whenever the user states a durable fact, preference, instruction, identity or profile detail, project detail, or recurring workflow likely useful later — you do not need an explicit 'remember this'. Skip transient chit-chat. For spending, income, refunds, or bookkeeping requests, use add_expense.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesA simple user-facing category or path for this memory, such as preferences, projects/xmemo, or personal/travel.
scopeNoOptional scope that narrows memory access; leave blank for the token default.
bucketNoMemory bucket or namespace to read from or write to; use % only for tools that support wildcard reads.public
dedupeNoWhether to check for and merge likely duplicate memories before saving.
contentYesText body to save, such as a memory, TODO/action item, event note, or state summary.
team_idNoOptional team/workspace identifier for team-scoped memory access.
agent_idNoOptional client-supplied agent label for memory attribution.
device_idNoOptional client-supplied device identifier for attribution.
memory_idNoExact XMemo memory reference shown by search or recall.
confidenceNoConfidence score for the saved or updated memory, from 0.0 to 1.0.
expires_atNoOptional ISO 8601 expiration timestamp for the memory.
importanceNoImportance score for the saved or updated memory, from 0.0 to 1.0.
memory_typeNoMemory type/category filter or value, such as episodic, identity, procedural, semantic, working, auto, or %.auto
device_labelNoOptional human-readable device label for attribution.
semantic_keyNoOptional stable semantic key used to identify or upsert a memory concept.
metadata_jsonNoOptional JSON object string with extra metadata for the operation.{}
embedding_jsonNoOptional JSON array or object containing a precomputed embedding; leave blank for normal use.
provenance_jsonNoOptional JSON object string describing memory source, evidence, or attribution.{}
agent_instance_idNoOptional stable, non-secret agent instance ID for per-client attribution.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate readOnlyHint=false and destructiveHint=false, so the description's behavioral burden is lower. The description adds valuable context about saving for future recall and what types of information to save. It does not contradict annotations. However, it could mention more about side effects or persistence, but given annotations, a score of 4 is appropriate.

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 two sentences long, front-loaded with the primary purpose, and includes clear usage guidelines. Every sentence is necessary and efficient, with no wasted words.

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 tool's complexity (19 parameters, 48 sibling tools), the description is complete. It clearly explains the tool's role in the memory ecosystem, when to use it vs add_expense, and the output schema covers return values. No missing context is needed for an agent to select and invoke it correctly.

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 baseline is 3. The description mentions only content and path implicitly but does not elaborate on parameter semantics beyond the schema. Since the schema fully documents all 19 parameters, this is acceptable, and the description does not add significant value over the schema.

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: 'Save a memory so it can be recalled in future conversations.' It specifies concrete use cases (durable facts, preferences, instructions, etc.) and distinguishes it from sibling tool add_expense, meeting the criteria for a specific verb+resource with sibling differentiation.

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 provides explicit guidance on when to use the tool ('Call this whenever the user states a durable fact...') and when not to ('Skip transient chit-chat. For spending, income... use add_expense.'). This includes alternatives and exclusions, earning the highest score.

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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