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moorcheh-ai
by moorcheh-ai

recall_as_of

Retrieve memories known before a specified timestamp. Use to answer historical questions about past knowledge or to reconstruct prior context.

Instructions

Point-in-time recall: return only memories that were known before the given timestamp. Use this when the user asks historical questions like 'what did we know on 2025-11-01?' or to reconstruct context at a previous moment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional type filter.
as_ofYesCutoff timestamp. Accepts YYYY-MM-DD (interpreted as end of that day) or full ISO 8601 e.g. 2025-11-01T14:30:00Z.
limitNo
agent_idNoMemanto agent identifier the memory belongs to (required: no MEMANTO_DEFAULT_AGENT_ID is configured).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNosemantic | recent | as_of | changed_sincesemantic
countNo
queryNo
statusYes
messageNo
agent_idYes
memoriesNo
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the core behavior: returning memories known before a given timestamp. The parameter descriptions (notably for 'as_of') provide additional detail on timestamp interpretation. No contradictions or omissions about side effects (it is read-only). The description is adequate for understanding the tool's behavior.

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, front-loading the purpose ('Point-in-time recall') followed by immediate usage guidance. Every word serves a purpose; no filler or repetition. Excellent conciseness.

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's 4 parameters and existence of an output schema, the description covers the essential information: purpose, when to use, and key behavior. It does not detail return structure or parameter limits, but those are covered by the schema and output schema. The description is sufficient for an agent to make correct selection and invocation decisions.

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 75% (3 of 4 parameters have descriptions in the schema). The tool description adds value by contextualizing the 'as_of' parameter with usage examples, but does not describe 'type', 'limit', or 'agent_id' beyond what the schema already provides. For a high-coverage schema, a baseline of 3 is appropriate, with slight bonus for the usage context on 'as_of'.

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: 'return only memories that were known before the given timestamp.' It explicitly contrasts with siblings by focusing on point-in-time recall, and provides concrete examples of when to use it (historical questions, reconstructing context). This distinguishes it from other recall tools like 'recall' (current memories) or 'recall_recent' (recent memories).

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 provides explicit when-to-use guidance: 'Use this when the user asks historical questions... or to reconstruct context at a previous moment.' It does not explicitly mention when not to use it or name alternative tools, but the context is clear enough for an agent to infer that non-historical queries should use other recall tools.

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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