Fetch canonical statistical property types and market names used for sportsbook and DFS player props. Use this to identify valid line names before querying player stats or odds by title.
Canonical prop stat_types and /lines market names agents should use.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.6.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the content is canonical names but does not explicitly describe the return structure, whether the list is static, or any side effects. This leaves the agent to infer that calling it returns a list of strings.
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 short sentence with no filler. It efficiently packs both the subject (canonical prop stat_types and /lines market names) and intended usage ('agents should use') without redundancy.
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 has no parameters and no output schema, the description would need to describe the response shape to be fully actionable. It does not, leaving uncertainty about whether the response is a flat list or a structured object. It is minimally adequate but has a clear gap.
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 description is not required to explain parameter semantics. Baseline of 4 applies, and no misleading information is present.
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 identifies the tool as the authoritative source for prop stat_types and /lines market names, differentiating it from sibling list tools like list_sports and list_books by specifying the exact domain of returned values.
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 phrase 'agents should use' indicates this is the go-to reference for canonical names, but it does not explicitly state when to prefer this over sibling list tools or how it relates to query-building tools like get_lines. Clear context, but no exclusions or explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.