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total-agent-memory

total-agent-memory

by vbcherepanov
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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memory_skill_get

Read-onlyIdempotent

Retrieve a stored skill by its exact name or match a natural language trigger, or list all available skills from persistent agent memory.

Instructions

Find skills matching a trigger. Skills are learned procedures — HOW to do things.

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_skill_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNoGet skill by exact name
triggerNoNatural language trigger to match
list_allNo

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?

Annotations already declare readOnlyHint and idempotentHint. The description is consistent with these but adds no further behavioral context (e.g., return format, behavior on no match, or fuzzy matching semantics).

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 concise, consisting of two short sentences. It defines the key concept (skills) without unnecessary verbosity, though it could benefit from a structured parameter breakdown.

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 omits critical context: it does not specify what the tool returns (e.g., a list of skill names or full objects), how parameters interact, or when to prefer this over siblings like memory_skill_update or memory_search_by_tag. With no output schema, this incompleteness is especially problematic.

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 description only clarifies the 'trigger' parameter by mentioning 'matching a trigger.' It does not explain 'name' (e.g., exact match) or 'list_all' (e.g., return all skills), which is a significant gap given the schema lacks any parameter descriptions.

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?

Description clearly states the tool 'Find skills matching a trigger' and defines skills as 'learned procedures — HOW to do things.' This gives a clear verb and resource, though it doesn't explicitly distinguish it from sibling tools like memory_get or memory_search_by_tag.

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, nor on how the parameters (name vs trigger vs list_all) should be chosen. The description implies trigger-based search but leaves parameter semantics entirely implicit.

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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