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total-agent-memory

total-agent-memory

by vbcherepanov
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Python
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memory_eval_entity_consistency

Read-onlyIdempotent

Verifies entity deduplication canonicalization remains stable across repeated saves of variant tag spellings.

Instructions

v11.0 Phase 8: verifies entity_dedup canonicalization is stable across repeated saves of variant tag spellings.

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_eval_entity_consistency"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNofast

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 indicate read-only, idempotent, and non-destructive behavior, so the bar is lower. The description's 'verifies' aligns with these annotations, but it does not add context about what happens on failure, whether a report is returned, or any side effects beyond the annotations.

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 sentence with no extraneous words, and the main verb 'verifies' is front-loaded. It is compact and to the point, though the density of technical terms slightly reduces clarity.

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?

No output schema or return value is described, which is important for an evaluation tool. The description also lacks context about how this fits into the broader memory evaluation workflow or what 'canonicalization stability' means in practice, making it incomplete for an agent operating in a complex domain.

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 schema fully documents the 'mode' parameter with an enum (fast/balanced/deep) and a default value, so coverage is high. The description adds no additional meaning or usage detail for the parameter, leaving the baseline score of 3 appropriate.

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 clearly states a specific verb ('verifies') and a specific resource ('entity_dedup canonicalization'), and the phrase 'across repeated saves of variant tag spellings' narrows the scope. It is distinct from sibling evaluation tools by focusing on entity consistency, though the jargon is dense and not fully explained.

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

Usage Guidelines1/5

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 the many sibling evaluation tools (e.g., memory_eval_long_context, memory_eval_temporal). There is no mention of use cases, prerequisites, or alternative selection criteria, leaving the agent without direction on when to invoke it.

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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