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mnemox-ai

TradeMemory Protocol

by mnemox-ai

get_behavioral_analysis

Read-onlyIdempotent

Retrieve aggregate trading behavior stats (hold times, disposition ratio, lot sizing variance, Kelly criterion comparison) to identify and correct behavioral biases.

Instructions

Get behavioral analysis from procedural memory.

Returns aggregate trading behavior stats: hold times, disposition ratio, lot sizing variance, and Kelly criterion comparison.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoFilter by symbol. Returns all if omitted.
strategy_nameNoFilter by strategy name. Returns all if omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by specifying the data source ('procedural memory'), the aggregate nature of the stats, and the exact metrics returned, which is context beyond the structured annotations.

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 two efficient sentences. The first sentence states the action and source, and the second lists the specific return values. No unnecessary words or redundant information, and the key verb is front-loaded.

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

Completeness5/5

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

With a read-only, idempotent, non-destructive annotation set, an output schema, and fully documented parameters, the description provides sufficient context for the agent to correctly select and invoke the tool. It explains the source, the aggregate nature, and the key metrics returned, leaving no critical gaps.

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?

Schema description coverage is 100% (both symbol and strategy_name are described with 'Returns all if omitted'). The description itself does not add parameter details or syntax, and the schema already fully documents the parameters. Baseline 3 applies because the schema carries the heavy lifting.

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 with a specific verb ('Get') and a well-defined resource ('behavioral analysis from procedural memory'). It enumerates the specific output metrics (hold times, disposition ratio, lot sizing variance, Kelly criterion comparison), which distinguishes it from sibling tools like get_strategy_performance or get_trade_reflection.

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

Usage Guidelines3/5

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

The description implies usage context by specifying the source (procedural memory) and aggregate nature, but it does not explicitly state when to use this tool over alternatives or provide exclusions. There is no mention of alternative tools or conditions where another tool would be more appropriate.

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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