Analyze Prop
Model a single player's prop vs tonight's FanDuel line -> edge.
200: Successful Response (Success Response) Content-Type: application/json 422: Validation Error Content-Type: application/json
Example Response:
{
"detail": [
{
"loc": [],
"msg": "Message",
"type": "Error Type",
"ctx": {}
}
]
}| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| prop | No | home_run | |
| season | No | ||
| threshold | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose if the tool mutates data, requires authentication, or has side effects. The response format is standard and adds no behavioral context.
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 opening line is clear, but the inclusion of response status codes and an example response adds length without aiding tool selection. It is adequately structured but not maximally concise.
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 4 parameters, no output schema, and 26 sibling tools, the description is incomplete. It fails to explain parameter usage, edge computation, or selection criteria relative to similar 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%, and the description provides no explanation for 'name', 'prop', 'season', or 'threshold'. The agent cannot infer parameter semantics without additional knowledge.
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 clearly states the tool models a single player's prop against a FanDuel line to compute an edge. It distinguishes from siblings like 'betting_scan_edges' and 'betting_best_bets' by focusing on a single player prop.
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?
No explicit guidance is provided on when to use this tool versus alternatives. It does not mention exclusions or prerequisites, leaving the agent to infer usage from the brief purpose statement.
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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