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moorcheh-ai
by moorcheh-ai

batch_remember

Store multiple independent memories at once, up to 100 items. Use this tool to persist lists of facts extracted from documents or other structured data.

Instructions

Store many memories at once (up to 100). Use this when you have a list of independent facts to persist - e.g. extracting structured data from a document. For a single item, prefer remember.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idNoMemanto agent identifier the memory belongs to (required: no MEMANTO_DEFAULT_AGENT_ID is configured).
memoriesYesList of memory dicts. Each item supports the same fields as `remember` (content [required], type, title, confidence, tags, source, provenance). Max 100 items.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
failedNo
statusYes
messageNo
resultsNo
agent_idYes
namespaceNo
successfulNo
total_submittedNo
Behavior3/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions the limit of 100 items but omits details about error handling, atomicity, or idempotency, which are relevant for a batch 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences that front-load the core action and capacity, then provide usage guidance and sibling reference without extraneous words.

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?

Given the existence of an output schema and the tool's straightforward purpose (batch memory storage), the description covers the essential aspects: capacity, use case, and sibling distinction. Minor missing details about potential side effects or failure modes prevent a higher score.

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 schema already documents both parameters adequately. The description adds no further parameter-level meaning beyond the schema's details, so baseline score applies.

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 stores multiple memories at once (up to 100) and distinguishes it from the sibling tool `remember` by specifying that single items should use that alternative.

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 advises when to use this tool ('list of independent facts to persist') and when to prefer an alternative ('for a single item, prefer remember'), including a concrete example.

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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