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lflabs-memory

lflabs-memory

by LF-Labs-Inc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

recent

List up to 50 newly added or updated memories to review changes in stored long-term memory.

Instructions

List the most recently added or updated memories (at most 50).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "recent"
  }
}

Input Schema

NameRequiredDescriptionDefault
nNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.7

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It usefully discloses the 50-item ceiling, but says nothing about ordering direction, whether additions and updates are interleaved, or whether truncation is silent. The output schema covers the return shape, so that omission is acceptable.

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?

One short sentence with the cap front-loaded and no filler. It is efficient, though its brevity leaves real gaps rather than being optimally dense.

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?

For a simple one-optional-parameter list tool with an output schema, the essentials are present. Missing are the ordering guarantee and the n-versus-50 relationship, which an agent needs to size requests and interpret results correctly.

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?

The single parameter n has 0% schema description coverage — only a title "N" and default of 20. The description partially compensates by implying a result-count cap of 50, but never explains that n is the requested count or how it interacts with that ceiling.

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 gives a specific verb and resource ("List ... memories") plus a scope qualifier ("most recently added or updated"), which separates it from search-style siblings such as recall or search_chats. It stops short of naming an alternative explicitly, so the differentiation is implied rather than stated.

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?

Usage is only implied: an agent can infer this is the tool for a recency-ordered browse rather than a targeted lookup. There is no explicit when-to-use, when-not-to-use, or named alternative (e.g., recall) to route between them.

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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