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TradeLab-MCP

TradeLab-MCP

by CaioAllgayer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

validate_ea_standard

Verify an Expert Advisor's use of TradeLab's guarded stop, sizing, metadata, and bar helpers to confirm standard compliance.

Instructions

Check that an EA uses the guarded TradeLab stop, sizing, metadata, and bar helpers.

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": {
      "source": "<source>"
    },
    "name": "validate_ea_standard"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits itself. 'Check that' implies a read-only validation, but it does not state whether the tool parses source, requires a compiled EA, or returns pass/fail diagnostics, so agents lack key behavioral expectations.

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 description is a single front-loaded sentence with no filler, and it packs the core purpose and scope efficiently. Slightly more detail would be welcome, but conciseness itself is strong.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter validation tool, the description omits the meaning of the source parameter, any usage context, and behavioral outcomes. This leaves a capable agent to guess at invocation details and expected results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description never mentions the 'source' parameter or what format it expects. The phrase 'an EA' weakly implies source identifies the EA, but this is not explicit enough to reliably populate the required string parameter.

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 ('Check') and resource ('an EA'), and lists precise aspects being validated: guarded TradeLab stop, sizing, metadata, and bar helpers. This distinguishes it from validate_tester_ini and other siblings focused on terminal/runtime tasks.

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

Usage Guidelines2/5

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

No guidance is given about when to use this tool instead of validate_tester_ini or other validation/compile siblings. The intended context must be inferred entirely from the tool name and the list of checked features.

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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