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total-agent-memory

total-agent-memory

by vbcherepanov
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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memory_concepts

Read-onlyIdempotent

List or search concepts in the knowledge graph. Filter by node type or name, and optionally include linked memory records.

Instructions

List or search concepts in the knowledge graph.

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": "memory_concepts"
  }
}

Input Schema

NameRequiredDescriptionDefault
typeNoFilter by node type
limitNo
queryNoSearch concepts by name
include_memoriesNoInclude linked knowledge records

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to repeat these. However, the description adds no additional behavioral context (e.g., that it returns a list without side effects), which is acceptable but not enhancing.

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?

The description is a single concise sentence with no redundancy or fluff. It is efficiently structured, though it could benefit from a bit more detail without becoming verbose.

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?

Given the large number of sibling tools (many memory-related), the description is too sparse to provide adequate context. It does not hint at what 'concepts' specifically means, how this differs from other search tools, or any special behavior like returning linked memories when include_memories is true.

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

Parameters2/5

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

The schema provides descriptions for 3 of 4 parameters (type, query, include_memories), but the 'limit' parameter has no description, resulting in 75% coverage, below the 80% threshold. The description does not compensate by explaining any parameters, leaving the behavior of 'limit' ambiguous.

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 uses specific verbs 'List or search' and a clear resource 'concepts in the knowledge graph,' which distinguishes it from most sibling tools. However, it does not fully differentiate from other search-related tools like memory_search_by_tag or memory_recall, so it is not a perfect 5.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as memory_recall, memory_search_by_tag, or memory_timeline. The description lacks any contextual cues to help an agent decide when to invoke this specific tool.

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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