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mnemox-ai

TradeMemory Protocol

by mnemox-ai

Get Agent State

get_agent_state
Read-onlyIdempotent

Retrieve an AI trading agent's current confidence, risk appetite, drawdown, win/loss streaks, and equity to get a recommended action based on drawdown severity.

Instructions

Get the current agent affective state (confidence, risk, drawdown).

Returns confidence level, risk appetite, drawdown percentage, win/loss streaks, equity tracking, and a recommended action based on current drawdown severity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds the substantive behavioral detail that a 'recommended action based on current drawdown severity' is derived server-side, but says nothing about freshness, caching, or when state is recomputed.

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?

Two short sentences, the purpose front-loaded and the returned fields grouped after it. Nothing is padded or redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no inputs, an output schema present, and annotations carrying the safety profile, the description only needs to convey purpose and rough content — which it does. The one omission is how this read-only snapshot relates to the behavioral-analysis and performance siblings.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. The parenthetical field list adds mild color but no parameter meaning.

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?

States a specific verb and resource ('Get the current agent affective state') and enumerates the state dimensions returned (confidence, risk, drawdown). An agent understands the purpose immediately, but the description never distinguishes this from the conceptually similar sibling get_behavioral_analysis.

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?

There is no indication of when to call this versus alternatives such as get_behavioral_analysis, get_strategy_performance, or check_active_plans, nor any prerequisites. Usage is only implied by the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.