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remember

Store important facts, preferences, and decisions for later recall, ensuring key information persists across conversations.

Instructions

Store a memory for later recall. Use this to remember important facts, user preferences, decisions, or any information that should persist across conversations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoType of memory: fact (default), preference, task, event, context, or reflection
contentYesThe information to remember
importanceNoImportance from 0.0 to 1.0 (default: 0.5). Higher importance memories are prioritized in recall.
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that memories 'persist across conversations' and are 'for later recall,' which are key behavioral traits. It does not mention failure modes, deduplication, or capacity limits, but for a simple store operation this is sufficient.

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 concise sentences, front-loaded with the key action 'Store a memory.' Every phrase adds value, and it avoids restating schema properties or filler.

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?

For a simple 3-parameter tool with no output schema, the description covers the primary purpose, persistence behavior, and typical use cases. It is complete enough for an agent to select and invoke the tool correctly, though it omits potential edge cases like error handling or memory size limits.

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 description does not need to document parameters. The examples in the description map to the 'content' parameter, but the tool adds no extra semantic detail beyond the schema's own descriptions.

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 opens with a specific verb and resource: 'Store a memory for later recall.' It lists concrete examples (facts, preferences, decisions) that clarify scope and distinguish it from sibling tools like recall and forget, which are retrieval/deletion operations.

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 'Use this to remember...' and enumerates clear use cases such as important facts, preferences, and decisions. It does not explicitly name alternatives or exclusion scenarios, but the use cases strongly imply when this tool is appropriate.

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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