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LuxAlgo

LuxAlgo Library MCP

Official
by LuxAlgo

Journal P&L breakdown

journal_breakdown
Read-only

Break down closed trades by nine factors to find your strengths and weaknesses, with net P&L, win rate, and counts per group.

Instructions

Where the P&L actually comes from: closed trades in the window grouped nine ways — weekday, time of day, hold time, symbol, side, position size, tag, rating and asset class — each group with trade count, wins, losses, net P&L, average net P&L and win rate (breakevens excluded). Defaults to all time, since groups need sample size; narrow with range or from/to. The tool for 'what am I good or bad at' questions; journal_overview has the headline numbers. Requires signing in with a LuxAlgo account (OAuth).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoInclusive end day (YYYY-MM-DD, journal timezone). Overrides `range`.
fromNoInclusive start day (YYYY-MM-DD, journal timezone). Overrides `range`.
rangeNoNamed window ending today in the journal timezone. Ignored when from/to are given.
accountsNoJournal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint and openWorldHint, so safety is covered; description adds what annotations cannot: the auth requirement (LuxAlgo OAuth sign-in), the default-all-time behavior, the breakevens-excluded rule, and the sample-size rationale. Lacks disclosure of return format/pagination, but no output schema exists so this is a modest gap.

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?

Front-loaded with the core purpose and the nine-dimension enumeration, then defaults, then routing guidance, then auth. Every sentence earns its place. Slightly dense with the long enumeration and metric list, but no wasted filler.

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?

Covers purpose, grouping dimensions, returned metrics, default window, scoping, sibling routing, and auth — substantial for a 4-param read tool with no output schema. Missing only pagination/result-size limits, which is minor given the schema is fully documented.

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% and the schema already documents range/from/to override precedence and account id semantics. The description's 'narrow with range or from/to' corroborates but adds no syntax or format detail beyond the schema. Baseline 3.

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?

States a specific verb+resource ('P&L breakdown' of closed trades) and enumerates the nine grouping dimensions and the eight aggregate metrics returned. Differentiates from the sibling journal_overview by name, and positions it against 'what am I good or bad at' questions.

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

Usage Guidelines5/5

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

Explicit when-to-use ('what am I good or bad at' questions vs journal_overview for headline numbers), explicit defaults ('Defaults to all time, since groups need sample size'), and explicit scoping guidance (narrow with range or from/to). The narrow-vs-broad tradeoff is spelled out.

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