Fetch coffee price data for financial analysis using Alpha Vantage market data, supporting various intervals and data types.
Fetch coffee
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": "coffee"
}
}| 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?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. 'Fetch coffee' doesn't reveal whether this is a read/write operation, what permissions are needed, rate limits, error conditions, or what the return format might be. This is critically inadequate for a tool with parameters.
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?
While technically concise with just two words, this is under-specification rather than effective brevity. The description is front-loaded but provides no useful information, making every word wasted rather than earning its place through clarity or guidance.
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 tool's complexity (2 parameters, no annotations, no output schema) and rich sibling context (100+ financial tools), the description is completely inadequate. It doesn't explain what 'coffee' means in this financial context, what data it returns, or how to use the parameters, making the tool essentially unusable.
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?
The description mentions no parameters, while the schema has 2 parameters (interval, datatype) with 0% description coverage. The description fails to compensate for this complete lack of parameter documentation, leaving both parameters entirely unexplained and unusable.
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 coffee' is a tautology that merely restates the tool name 'coffee' without specifying what resource it actually fetches. It doesn't distinguish this tool from its many financial data siblings, leaving the purpose ambiguous and unhelpful for an AI agent.
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 no guidance on when to use this tool versus the 100+ sibling tools, which include various financial indicators, commodities, and data types. There's no indication of context, prerequisites, or alternatives, making it impossible for an agent to make an informed selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.