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list_memories

Find stored AI memories by applying filters like type, category, scope, or importance. Quickly access relevant context from your memory store.

Instructions

List stored memories with optional filters by type, category, scope, or project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
memory_typeNoFilter by type
categoryNoFilter by category (e.g., "backend", "frontend", or any custom category)
importance_minNoOnly return memories with importance >= this value
scopeNoFilter by scopeall
limitNoResults per page
tagNoFilter by tag (e.g., "marketing-campaign")
offsetNoPagination offset
untypedNoWhen true, only return memories with no memory_type set
sort_byNoSort order: importance (default), updated, created, referenced (most used first), least_usedimportance
Behavior2/5

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

No annotations are provided, so the description should disclose behavioral traits. It does not mention that the tool is a read-only operation, nor does it discuss pagination behavior, performance implications, or side effects. This is a significant gap.

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 a single concise sentence that efficiently conveys the tool's purpose without unnecessary words. It is well-structured and front-loaded.

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?

While the schema covers all parameters, there is no output schema and the description omits return format, pagination details, or sorting behavior. Given the tool's complexity (9 parameters, many siblings), the description is minimally adequate 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?

Schema description coverage is 100%, so the schema already documents all parameters well. The description adds no extra meaning beyond repeating that there are optional filters. Baseline 3 is appropriate.

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 clearly states the action (list) and resource (stored memories) with optional filters. However, among many siblings like recall_memories, it does not explicitly differentiate itself, which slightly reduces clarity.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as recall_memories or get_stale_memories. The description lacks context for appropriate invocation.

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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