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remember

Store episodic memories about users, projects, feedback, or yourself to retain context across AI agent sessions.

Instructions

Store an episodic memory that persists across sessions. Use this when you learn something important about the user, a project, or yourself that should be available in future sessions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ttlNoTime-to-live: "7d", "30d", "24h", "permanent", or omit for no expiration.
titleYesShort title for the memory
contentYesThe memory content — what you learned, observed, or were told
projectNoAssociated project, if any (omit for global memories)
categoryYesMemory category: user (about the human), project (about work), self (capability/learning), feedback (corrections/confirmations), reference (external pointers), pursuit (active goal or ongoing creative thread)
metadataNoArbitrary key-value metadata
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It mentions persistence across sessions but does not disclose side effects (e.g., overwriting, expiration via TTL, or authentication needs). The description lacks detail on what happens after storage.

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, front-loading the action and purpose. Every sentence carries weight with no wasted words.

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?

Given 6 parameters (including enums and nested objects) and no output schema, the description is minimal. It does not explain return values or post-invoke behavior, relying heavily on the schema. Adequate but not comprehensive.

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 description coverage is 100%, so the baseline is 3. The tool description adds no extra meaning beyond what the schema already provides for parameters.

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 verb 'Store' and the resource 'an episodic memory that persists across sessions', distinguishing it from sibling tools like 'forget' or 'recall'. It also provides a concrete usage scenario ('when you learn something important...').

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 explicitly says when to use the tool ('when you learn something important...'), providing clear context. However, it does not mention when not to use it or compare it to alternatives like 'knowledge_write'.

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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