Fetch real-time and historical wheat commodity data for financial analysis and market monitoring using Alpha Vantage API.
Fetch wheat
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": "wheat"
}
}| 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 the full burden of behavioral disclosure. 'Fetch wheat' gives no information about what the tool does beyond the name, such as whether it's a read-only operation, requires authentication, has rate limits, or what format the output takes. This is 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?
The description is extremely concise with just two words, 'Fetch wheat', which is front-loaded and wastes no space. However, this conciseness comes at the cost of being under-specified, but for this dimension alone, it scores high due to minimal verbosity.
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 (2 parameters with 0% schema coverage, no annotations, no output schema), the description is completely inadequate. It doesn't explain what the tool does, how to use it, what the parameters mean, or what to expect in return, making it insufficient for effective tool invocation.
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 input schema has 2 parameters ('interval', 'datatype') with 0% description coverage, meaning their purposes are undocumented. The description 'Fetch wheat' adds no meaning about these parameters, failing to compensate for the schema gap. This leaves the agent with no semantic understanding of the inputs.
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 wheat' restates the tool name 'wheat' with a generic verb 'fetch', making it tautological. It doesn't specify what resource is being fetched (e.g., price data, historical data, market information) or distinguish it from sibling tools like 'corn' or 'coffee', which likely have similar descriptions.
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 alternatives. It doesn't mention any context, prerequisites, or differences from sibling tools (e.g., 'corn', 'coffee'), leaving the agent with no usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.