Fetch real-time and historical cotton market data from Alpha Vantage for financial analysis and market monitoring.
Fetch cotton
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": "cotton"
}
}| 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 cotton' gives no indication of whether this is a read-only operation, whether it requires authentication, what rate limits might apply, what format the output takes, or any error conditions. This leaves critical behavioral traits completely unspecified.
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 cotton'), which could be appropriate if it were informative, but here it's under-specified rather than efficiently structured. While it's front-loaded with the only information available, that information is insufficient, making this a case of brevity at the expense of clarity.
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 two parameters, no annotations, no output schema, and numerous sibling tools in what appears to be a financial/commodity data domain, the description is completely inadequate. It doesn't explain what the tool returns, how parameters affect results, or how it differs from similar tools, leaving the agent with insufficient context for effective use.
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 schema has 0% description coverage, with two parameters ('interval' and 'datatype') completely undocumented in the schema. The description 'Fetch cotton' provides no information about these parameters—what values they accept, what they control, or whether they're optional/required. This fails to compensate for the schema's deficiencies.
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 cotton' is a tautology that restates the tool name without adding meaningful context. It provides a basic verb ('fetch') but doesn't specify what 'cotton' refers to (commodity data, price information, market metrics, etc.) or distinguish it from sibling tools like 'coffee', 'corn', or 'wheat' that appear to be in the same domain. The purpose remains vague beyond the most generic interpretation.
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 exclusions, and doesn't reference sibling tools that might serve similar purposes (e.g., 'coffee', 'corn'). Without this information, an agent cannot make informed decisions about tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.