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remember_batch

Save multiple memories with keys and metadata in one call. Returns saved IDs, reducing overhead compared to individual saves.

Instructions

Save multiple memories in one call. Each item: {content, keys, key_types?, namespace?, ttl_seconds?, related_to?}. Returns list of saved IDs. More efficient than multiple remember() calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full responsibility. It discloses that the tool saves memories and returns a list of saved IDs. It also outlines the item structure (content, keys, etc.), which is useful. However, it omits important behavioral aspects such as partial failure handling, whether the operation is atomic, or any validation or permission requirements.

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-loads the main purpose, and includes no redundant information. Every sentence adds value: the first explains the core action, the second details the item schema and return value.

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?

With an output schema present, the return values are likely covered, so the description's mention of returning saved IDs is a bonus. The tool is a batch operation with potential complexity (e.g., partial failures, limits), but the description does not address these. It is adequate for basic usage but not fully complete.

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?

The input schema provides no descriptions and has a coverage of 0%, so the description must compensate. It lists the expected fields for each item (content, keys, key_types?, namespace?, ttl_seconds?, related_to?), which adds meaning beyond the empty schema. However, it does not explain what each field means, which are required, or any constraints, leaving gaps for the agent.

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 function: 'Save multiple memories in one call.' It identifies the resource (memories) and the batch nature. It also distinguishes itself from the sibling tool remember() by stating it is 'More efficient than multiple remember() calls,' making the purpose unambiguous.

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 explicitly names the alternative tool (remember()) and positions remember_batch as the more efficient choice for batch saving. This gives the agent clear guidance on when to prefer this tool over the singular variant.

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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