live_market_scanFetch machine-readable market data live and derive business opportunities without manually entering the signal.
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": "live_market_scan"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 burden. It discloses that the tool fetches live data and derives opportunities, but it doesn't mention rate limits, latency, data format, or whether it is read-only. The phrase 'without manually entering the signal' hints at automation but not enough detail.
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?
One sentence, front-loaded with the action and resource, and no wasted words. It earns its place by explaining both the data fetch and the derived value.
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?
For a zero-parameter tool with no output schema, the description is mostly complete. However, it doesn't describe what the output looks like or any constraints (e.g., market scope, frequency). Given the tool's autonomous nature, a bit more context on output format or behavior would help.
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 tool has zero parameters, so the schema is trivially complete. The description adds the behavioral context of what the tool does with no input, which is sufficient. Baseline 4 for zero params is appropriate.
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 states a specific verb ('Fetch') and resource ('live market data'), and adds the purpose of deriving business opportunities. It is clear enough to distinguish from siblings like economic_opportunities and voice_margin_index, though it doesn't explicitly name them.
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 implies usage: use this tool when you need live market data and business opportunities without manual signal entry. It does not explicitly state when not to use it or name alternatives, but the context is reasonably clear.
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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