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memory_get_recent

Retrieve recent conversation messages for a specified agent to support persona mining and reflection. Use this tool to access message history for context management and self-evolving persona updates.

Instructions

Get recent messages for persona mining/reflection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYes
max_messagesNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. 'Get' clearly implies a read-only retrieval and 'recent messages' communicates the data scope. Still, the description does not state ordering, message scope, whether the operation is non-mutating, or any behavior around empty results.

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 short sentence, front-loaded with the action and resource. Every word contributes either to the tool's function or its intended use case, with no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

GPT-web: For a tool with no output schema, no annotations, and zero schema description coverage, the description is too minimal to make the tool reliably usable. It omits recentness semantics, output shape, parameter meaning, and any guidance versus sibling tools.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no parameter semantics at all. It never explains what agent_id means or how max_messages affects behavior, leaving the agent to infer everything from parameter names and defaults.

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 states a specific verb and resource: 'Get recent messages.' The intended purpose, 'for persona mining/reflection,' adds context and suggests a distinct use case. However, it does not explicitly differentiate itself from sibling tools like memory_get_context or memory_load.

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

Usage Guidelines3/5

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

The phrase 'for persona mining/reflection' provides an implied usage context, showing when an agent might choose this tool. It does not, however, describe when not to use it or specify alternatives among the many memory_* siblings.

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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