Fetch real-time and historical copper price data for financial analysis and market monitoring using Alpha Vantage API.
Fetch copper
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": "copper"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| interval | No | ||
| datatype | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Fetch' implies a read operation, but the description reveals nothing about authentication needs, rate limits, data freshness, error conditions, or what format/scope of data is returned. For a financial/commodity data tool with zero annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise ('Fetch copper' - just two words), but this represents under-specification rather than effective brevity. While front-loaded with the verb 'fetch', it lacks any meaningful content that would help an AI agent understand or use the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by sibling tools (financial/commodity data with various parameters), zero annotations, 2 undocumented parameters, and no output schema, the description is completely inadequate. It provides no information about what data is fetched, how parameters affect results, what format data returns in, or how this differs from similar commodity tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (both parameters have no descriptions), and the tool description provides zero information about the 'interval' and 'datatype' parameters. The description doesn't mention parameters at all, leaving both completely undocumented. With 2 parameters and no schema descriptions, the description fails to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch copper' is a tautology that merely restates the tool name with a generic verb. It doesn't specify what 'copper' refers to (commodity price, mining data, market information) or what resource is being fetched. Compared to siblings like 'coffee', 'corn', and 'wheat' which have similar vague descriptions, it fails to distinguish itself or provide meaningful purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. With 100+ sibling tools including many commodity-related ones (coffee, corn, wheat, aluminum), there's no indication whether this fetches price data, market analytics, or other copper-related information, or how it differs from tools like 'all_commodities' or 'time_series_daily'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.