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total-agent-memory

total-agent-memory

by vbcherepanov
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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analogize

Read-onlyIdempotent

Find past solutions and lessons from other projects by matching overlapping features with your problem text using Jaccard similarity.

Instructions

Find past solutions/lessons from OTHER projects whose feature set overlaps with the given problem text (Jaccard similarity).

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": {
      "text": "<text>"
    },
    "name": "analogize"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
limitNo
min_scoreNo
only_typesNo
exclude_projectNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds useful context about the algorithm (Jaccard similarity) and the scope (other projects), which goes beyond the annotations without contradicting them.

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, clear, and well-structured sentence. It efficiently communicates the core purpose without unnecessary words or complexity.

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?

The description gives a high-level purpose but lacks operational details. It does not explain the semantics of the parameters, what the output looks like, or any edge cases. An agent would likely be uncertain about how to properly configure the input beyond the single required 'text' parameter.

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?

The schema has 5 parameters but zero description coverage. The description only mentions 'given problem text' and 'Jaccard similarity,' leaving the meaning and usage of limit, min_score, only_types, and exclude_project completely unexplained. The description fails to compensate for the lack of schema descriptions.

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's function: finding past solutions/lessons from other projects using feature-set overlap and Jaccard similarity. It is specific and distinguishes this tool from sibling memory tools that focus on the current project's memory.

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?

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention any conditions or prerequisites. It lacks explicit direction for an agent to decide when analogize is the appropriate choice.

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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