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nexus-xyz

nexus-exchange-mcp

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by nexus-xyz

fetch_portfolio_history

Retrieve an authenticated account's portfolio time-series—equity, cumulative trading PnL, and traded volume—over day/week/month/all windows; heavy read, poll sparingly.

Instructions

Get the authenticated account's portfolio time-series — equity, cumulative trading PnL, and cumulative traded volume — over a selectable window, oldest first. Richer than fetch_equity_history (equity only, 5s cadence, ~1h); both derive equity from the same source, so the two never disagree. Each window sets its own downsample cadence and point capacity: day 5m/288, week 1h/168, month 6h/120, all 1d/366. pnl is deposit-neutral (trading performance only) and volume is monotonically non-decreasing. This is a HEAVY read — the gateway charges it 5x an ordinary GET, so a single call draws about five requests' worth of budget and the remaining reported by fetch_rate_limit_status (counted in ordinary requests) drops by ~5. Poll it sparingly. Requires API credentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of points to return (1–366). Clamped server-side to the selected window's capacity. Omit for the full window.
windowNoTime window to return, which also selects the cadence and point capacity. Defaults to `day` server-side when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations present, the description carries the full behavioral burden and does so richly: it discloses the 5x gateway charge and the resulting ~5 drop in `remaining` from `fetch_rate_limit_status`, the credential requirement, the deposit-neutral semantic of `pnl`, the monotonic nature of `volume`, and the per-window cadence/capacity table. These are exactly the traits an agent cannot infer from the schema.

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 content is front-loaded with purpose and output fields before qualifications, and every sentence carries information. It is dense — several facts are packed into single sentences and the cadence table sits mid-paragraph — but nothing is redundant padding.

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?

There is no output schema and no annotations, yet the description covers the returned fields, their ordering (oldest first), the cadence/capacity per window, the required credentials, and the rate-limit cost. Nothing an agent needs to call this correctly or interpret the result is missing.

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?

Schema coverage is 100%, so the baseline is 3; however, the description adds meaning beyond the schema by mapping each window to its own downsample cadence and point capacity (day 5m/288, week 1h/168, month 6h/120, all 1d/366) and by explaining that `limit` is clamped to that capacity. This is genuinely additive rather than restated schema text.

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 names a specific verb and resource (authenticated account's portfolio time-series) and enumerates exactly what is returned: equity, cumulative trading PnL, and cumulative traded volume. It explicitly distinguishes itself from the closest sibling `fetch_equity_history` by scope, cadence, and window, so an agent can route without opening either schema.

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 gives clear context for choosing between this and `fetch_equity_history` (richer, same equity source, so never disagreeing) and warns to poll sparingly because of the 5x cost. It lacks an explicit conditional such as 'if you only need equity, prefer fetch_equity_history', but the sibling comparison effectively conveys the trade-off.

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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