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Coinversaa

Coinversaa Pulse

Official
by Coinversaa

Hourly Profitability

pulse_hour_profitability
Read-onlyIdempotent

Analyze realized PnL across 24 UTC hours to identify the most profitable time to close positions. Provides lifecycle count, total/avg PnL, wins, and losses for session-bias analysis.

Instructions

Global PnL heatmap by UTC hour of position close. Returns, for each of the 24 hours, lifecycle count, total PnL, avg PnL, wins, and losses. Use for 'what time of day is most profitable to close?' / session-bias analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
useToonFormatNoReturn data in compact toon format (default: true). Set to false for standard JSON.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.8.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context by clarifying that results are global, based on UTC hour of position close, and include specific aggregate metrics for each of the 24 hours.

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 sentences with no filler: the first states what the tool returns and the grouping dimension, the second gives the concrete use case. Every sentence provides value.

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?

Given the low complexity, zero required parameters, and strong annotations, the description sufficiently explains what the tool returns and when to use it. It even enumerates the computed fields, which compensates for the absence of an output schema.

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 single parameter, useToonFormat, is fully described in the schema with 100% coverage, so the description does not need to add parameter detail. It correctly focuses on the output semantics rather than repeating the schema.

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 uses a specific verb-resource combination: returns a global PnL heatmap grouped by UTC hour of position close. It clearly identifies the analytical dimension and differentiates itself from sibling analytics tools by focusing on time-of-day profitability.

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

Usage Guidelines4/5

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

It explicitly states the intended use case: answering 'what time of day is most profitable to close?' and session-bias analysis. It does not mention when not to use it or name alternative tools, but the context is clear enough for an agent to select it appropriately.

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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