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memory_store

Store memories with type and metadata for later retrieval. Use to recall transactions, vendor experiences, preferences, errors, and decisions.

Instructions

Store a memory for later retrieval.

Use this to remember transactions, vendor experiences, decisions, spending patterns, API responses, or any information worth recalling.

Args: content: The memory content to store. Be descriptive. Examples: - "Paid 500 sats to bitrefill.com for a $5 Amazon gift card via L402. Fast, reliable." - "OpenAI API returned 429 rate limit after 50 requests/min. Backoff to 30/min." - "User prefers to cap spending at 10,000 sats per session." type: Memory category. One of: - general: Default, uncategorized - transaction: Payment records, invoices, L402 purchases - vendor: Service/API reputation and reliability notes - preference: User or agent preferences and settings - error: Error patterns and failure modes - decision: Key decisions and their reasoning metadata: JSON string of additional key-value pairs. Example: '{"vendor": "bitrefill.com", "amount_sats": 500}'

Returns: The stored memory record with id, content, type, and timestamps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
typeNogeneral
metadataNo{}
Behavior3/5

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

No annotations provided. Description lacks details on destructive behavior, idempotency, or authentication needs. It only states it stores and returns a record, which is minimal but not misleading.

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?

Well-structured with Args and Returns sections, front-loaded purpose. Examples add clarity but could be slightly more concise.

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 many memory-related sibling tools, description sufficiently covers purpose and parameters. Return value is specified, though no output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 0% description coverage. Description provides detailed explanations for content, type categories, and metadata with examples, far exceeding schema info.

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 it stores a memory for later retrieval, with specific examples. It distinguishes from sibling tools like memory_list, memory_query, memory_edit.

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?

Provides explicit use cases (transactions, vendor experiences, decisions, etc.) but does not mention when not to use it or alternatives. Sibling tool names hint at alternatives.

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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