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CarryMem

CarryMem

by lulin70
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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classify_and_remember

Classify messages and automatically store valuable ones for future recall. Single-step process to analyze, save, and return results.

Instructions

Classify a message AND store it if worth remembering. One-step operation: classify → store → return. Requires storage adapter to be configured.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "message": "<message>"
    },
    "name": "classify_and_remember"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextNoConversation context (optional)
messageYesThe message content to classify and store

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description discloses the three-step workflow and the dependency on storage adapter configuration. However, it does not explain the criteria for 'worth remembering' or behavior on failure, leaving gaps.

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 three sentences, front-loaded with the main purpose, followed by workflow and prerequisite. No redundant information, every sentence adds value.

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?

Given no output schema and no annotations, the description covers the basic workflow and prerequisite but lacks details on classification criteria, return values, and differentiation from many sibling tools. Adequate but not comprehensive.

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 description adds no meaning beyond the schema. Both parameters have clear descriptions in the schema, meeting the baseline for high coverage.

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 combines classification and storage in one step, using specific verbs and resource. It distinguishes itself from siblings like classify_message (only classification) and forget_memory (storage removal).

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 description implies usage for combined classification and storage but does not explicitly state when to use it versus alternatives. The requirement of a storage adapter provides some context, but no exclusions or when-not-to guidance is given.

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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