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Lians-ai

Lians Agent Memory

Official

recall

Retrieve currently valid memories for a query, excluding superseded facts at the database level. Call before answering any memory-dependent question, and optionally filter by metadata such as ticker.

Instructions

Retrieve the most relevant CURRENT memories for a query. Returns only presently-valid facts — superseded facts are excluded at the DB layer. Call this before answering any question that may be in memory. Use filters={ticker: NVDA} to narrow to a specific instrument.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
queryYes
filtersNoMetadata equality filters, e.g. {ticker: NVDA}
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly explains that superseded facts are excluded at the DB layer and only currently-valid memories are returned, which is valuable behavior beyond the basic 'retrieve' action. It does not cover auth or rate limits, but for a read-only-like tool the core behavior is well disclosed.

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 plus an example, entirely front-loaded and free of fluff. Every clause adds meaning: what it retrieves, the current-validity constraint, when to call it, and how to narrow results.

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 tool is a retrieval operation with no output schema and simple parameters, the description covers most key aspects: purpose, behavior, usage timing, and a filter example. Missing details are k's effect on result count and return format, but for a tool of this simplicity it is reasonably 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 only 33% (only filters has a description). The description adds a useful example for filters ({ticker: NVDA}), but does not explain k or query beyond the schema. Since k has a default and query is self-explanatory, the compensation is moderate but incomplete.

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 purpose: 'Retrieve the most relevant CURRENT memories for a query.' It uses a specific verb and resource, and the emphasis on 'CURRENT' distinguishes it from siblings like recall_at or memory_lineage, which deal with historical or lineage data.

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?

The description gives explicit when-to-use guidance: 'Call this before answering any question that may be in memory.' It also provides a concrete filter example. However, it does not explicitly mention when not to use it or directly contrast with alternatives like recall_at or reconstruct.

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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