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Store Multiple Memories

montycat_remember_bulk

Store multiple records at once to persist memories with automatic embedding and indexing enabling semantic search and time-based recall.

Instructions

Store many memories at once; all are embedded and indexed automatically.

Args: values: A list of records (JSON objects) to store. keyspace: Memory namespace (defaults to the configured one). timestamp: Index a _created_at on each record for time-range recall. Defaults to MONTYCAT_AUTO_TIMESTAMP (on). Pass False for large imports that will never be recalled by time — it skips a server-side timestamp parse per record. wait_for_index: For persistent keyspaces, wait for secondary indexes before returning. Defaults to the engine setting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNo
valuesYes
vectorsNo
keyspaceNo
timestampNo
wait_for_indexNo
Install Server

TDQS

A3.8/5.0
Behavior5/5

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

The description goes well beyond the minimal annotations by explaining that all records are embedded and indexed automatically, how timestamp affects indexing, what wait_for_index does, and the performance rationale for disabling timestamp. This is rich behavioral context for a write operation.

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 well-structured with an opening summary followed by a clear Args list. It is appropriately sized, and each parameter explanation is concise and relevant, though the two undocumented parameters add slight imbalance.

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?

For a 6-parameter tool with no output schema, the description covers the core parameters and side effects but omits 'scope' and 'vectors', and doesn't mention return values or failure behavior. It is usable for basic invocation but not complete for advanced use cases.

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 0%, so the description must compensate. It clearly explains 'values', 'keyspace', 'timestamp', and 'wait_for_index', but leaves the 'scope' and 'vectors' parameters completely undocumented, which is a notable gap for an agent trying to use them correctly.

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 states a specific action ('Store many memories at once') and resource ('memories'), making the bulk variant clear. The name and title reinforce the bulk aspect, but it doesn't explicitly differentiate from the sibling montycat_remember, relying on the word 'bulk'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Store many memories at once' implies the use case for storing multiple records, but it doesn't explicitly say when to choose this over montycat_remember or montycat_forget. No alternatives or exclusions are provided, leaving the routing to inference.

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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