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BotSpot: AI Trading, Backtests and Bots

by io.github.grzesir
OverviewDiscussionsAdmin

Compare backtests

show_backtest_comparison
Read-onlyIdempotent

Answers "Which of my backtests did better?" for 2 to 10 saved backtests: equity lines started at 100 on the same chart plus a metric table (total return, CAGR, max drawdown, Sharpe, trades). Runs of one strategy with different parameter values are named by those values. Results are simulated. Read-only. Shows an interactive panel in apps that support MCP Apps; always returns a text summary and a botspot.trade link.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "backtestIds": "<backtestIds>"
    },
    "name": "show_backtest_comparison"
  }
}

Input Schema

NameRequiredDescriptionDefault
backtestIdsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / backtestIds / maxItems
      Previous value: -5New value: +10
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the readOnlyHint/destructiveHint/idempotentHint annotations, it discloses that results are simulated and that output has two modes: an interactive panel where MCP Apps is supported, and always a text summary plus a botspot.trade link. That is genuinely useful context an agent cannot get from annotations. It does not cover latency, cost, or what happens if an ID is not a saved backtest.

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?

It is front-loaded with the user-facing question and then the payload description, with no filler sentences. The final sentence packs two distinct output-channel facts compactly; slightly denser than ideal but every clause carries information.

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?

For a one-parameter tool with no output schema, the description covers inputs, the content of the result, the rendering modes, and the simulated-data caveat. Nothing an agent needs to decide to call it or interpret the response 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 description coverage is 0%, so the description must carry the meaning, and it does: the "2 to 10 saved backtests" phrasing reinforces the array bounds and adds the constraint that entries must be saved (not in-flight) backtests. It does not clarify ordering, duplicate handling, or what error surfaces for invalid UUIDs.

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 opens with the exact question the tool answers ("Which of my backtests did better?") and states the concrete outputs: equity lines rebased to 100 on one chart plus a metric table (total return, CAGR, max drawdown, Sharpe, trades). An agent can distinguish this from show_backtest_dashboard or show_backtest_chart_series without opening a 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 scopes usage precisely with "for 2 to 10 saved backtests," which tells the agent the minimum data required and that the backtests must already exist. It also implies when the naming-by-parameter-values formatting applies. It stops short of naming an alternative for single-backtest inspection, so there is no explicit when-not guidance.

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

All BotSpot: AI Trading, Backtests and Bots toolsInspect
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