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by io.github.MangroveTechnologies
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get_backtest_trades

Read-onlyIdempotent

The individual trades a backtest made -- entry and exit prices and times, profit or loss, and why each one closed. Use it when the user asks what a backtest actually traded; get_backtest has the summary metrics. THESE ARE SIMULATED TRADES from a backtest, not real ones -- list_trades has those. A long run is paged: at most 100 trades per call (default 25); pass offset to read on.

[Access: pay 0.001 USDC via x402 (PAYMENT-SIGNATURE header) OR authenticate with an API key. An x402-capable client will auto-pay; API-key clients pay nothing per call.]

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": {
      "backtest_id": "<backtest_id>"
    },
    "name": "get_backtest_trades"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum results.
offsetNoPagination offset in the result units documented by the tool; zero starts the first page.
backtest_idYesThe run's UUID, as run_backtest returned it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / limit / default
      Previous value: -100New value: +25
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description goes well beyond them: it warns the data is SIMULATED rather than real, discloses the 100-trade per-call cap and 25 default, explains offset continuation, and states the access model (0.001 USDC via x402 or API key). These are exactly the cost, scope, and pagination traits annotations cannot express.

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 resource definition, then routing guidance, then the simulated-vs-real caveat, then pagination, then access. Every sentence carries signal, though the bracketed payment block is verbose relative to the rest and could be tightened.

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?

Even without an output schema, the description enumerates the return payload (prices, times, P/L, exit reason), covers pagination limits, and discloses the payment/auth prerequisite. For a 3-parameter read tool this is everything an agent needs to call it correctly and interpret the result.

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 baseline would be 3. The description adds real meaning the schema omits: the concrete maximum of 100 results per call and the fact that offset advances through 'a long run', plus the default of 25. It is slightly short of 5 because limit/offset units are only loosely framed ('trades per call').

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 -- 'the individual trades a backtest made' -- and enumerates the returned fields (entry/exit prices and times, P/L, exit reason). It explicitly distinguishes itself from get_backtest (summary metrics) and list_trades (real trades), so an agent can pick it without opening any schema.

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?

Gives an explicit trigger ('when the user asks what a backtest actually traded'), names the alternative for the summary case (get_backtest), and names the alternative for real trades (list_trades). Both the when and the when-not are covered with named siblings.

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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