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quantitats

quantitats-mcp

Official
by quantitats

Read one bot's performance

get_bot_analytics
Read-onlyIdempotent

Fetch a bot's realized profit and loss and fill statistics, optionally over a specified time window, to evaluate trading performance.

Instructions

That bot's realized profit and loss and its fill statistics, optionally over a time window. Money figures are decimal strings keyed by asset or symbol; add two together only when they share one.

Requires the bots:read scope.

Rate limit: 600 requests per minute for your key, shared across every tool in the default group. Ten a second. These read stored records rather than calling a venue, which is why they are cheap.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe bot's name, as list_bots or create_bot answered it.
sinceNoRFC 3339 lower bound. Absent means no lower bound.
untilNoRFC 3339 upper bound. Absent means no upper bound.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior5/5

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

Goes well beyond the annotations: it discloses the required `bots:read` scope, the exact rate limit (600/min shared across the whole `default` group, ten per second), and explains these are stored-record reads rather than venue calls, hence cheap. That is exactly the operational context annotations cannot carry.

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-loads the outcome (P&L plus fill stats), then constraints. Most sentences earn their place, but 'Ten a second' merely restates the 600/min figure and is 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 output schema, the description usefully characterizes the return payload (realized P&L, fill statistics, decimal-string money keyed by asset/symbol) and covers auth plus rate limits. It stops short of describing what the fill statistics contain, leaving a small gap for a data-returning tool.

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%, so `name`, `since`, and `until` are already documented. The description echoes the optional time window and adds a return-value caveat about decimal strings keyed by asset, but contributes nothing new about the input parameters themselves. Baseline 3.

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 resource and scope: 'That bot's realized profit and loss and its fill statistics, optionally over a time window.' An agent can distinguish this from get_bot_config or list_bot_orders by the performance-metrics framing. It does not name a sibling to route away from, so it stays short of the top score.

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 mention of an optional time window implies when to use it (historical performance review), but there is no explicit when-to-use/when-not guidance and no named alternative among the 25 siblings. Adequate but inference-only.

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