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gold-mcp

gold-mcp

by ThaiTrevor
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_gold_correlations

Analyze gold daily return correlations against a macro basket for a chosen lookback period, revealing how gold aligns with economic indicators.

Instructions

Correlation of gold daily returns vs the macro basket.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_gold_correlations"
  }
}

Input Schema

NameRequiredDescriptionDefault
lookback_daysNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.2

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description must carry full behavioral disclosure. It only states what is being correlated; it does not explain the macro basket composition, computation method, output format, lookback behavior, or whether this is a safe read-only operation. This is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with no filler. It is front-loaded and communicates the core purpose efficiently.

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?

Given no output schema, no annotations, and only one line of prose, the description leaves major unanswered questions: what exactly is in the 'macro basket', what does the returned correlation look like, and how does the lookback affect results. The tool is too under-specified for reliable autonomous use.

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?

The schema has one parameter, lookback_days, with 0% schema description coverage and no mention in the description. While the parameter name implies a time window, the description fails to clarify the unit (trading vs calendar days), any allowed range, or the default behavior beyond the schema default.

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?

The description clearly identifies the tool's output as the correlation of gold daily returns versus a macro basket, which distinguishes it from siblings like get_gold_price, get_gold_ohlcv, and get_gold_seasonality. It lacks an explicit verb such as 'calculates' or 'returns', but the meaning is unambiguous.

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 on when to use this tool versus alternatives like get_macro_context or get_gold_price. There is no mention of exclusions, prerequisites, or scenarios where another tool would be more appropriate.

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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