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kashrockapi

kashrock-mcp

Official
by kashrockapi

get_props

Get DFS player props for any sport. Apply book, market, or player filters to target specific props, while slim mode and limit keep payloads compact.

Instructions

DFS player props only. Prefer book/market/player filters — default slim+limit keeps payloads small.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bookNo
slimNo
limitNo
sportYes
marketNo
offsetNo
playerNo
market_containsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.5

TDQS

C2.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It only notes that defaults keep payloads small, implying a read operation but never explicitly stating that it is non-mutating. It does not mention pagination via offset, return format, rate limits, or any side effects. The description fails to carry the full behavioral burden in the absence of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) and avoids fluff, which is good. However, the brevity leads to vagueness—key details about parameter semantics and tool selection are missing. It is concise but not effectively structured to convey essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 8 parameters, no output schema, and no annotations, the description is far from complete. It does not explain what the response looks like, how pagination works (offset), how 'market_contains' differs from 'market', or any constraints on values. An agent cannot reliably invoke this tool correctly with the provided information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions 'book/market/player filters' and 'slim+limit' but does not clarify the required 'sport' parameter, the 'offset' pagination parameter, or 'market_contains'. With 8 parameters and no schema documentation, this partial explanation is insufficient for correct usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it returns 'DFS player props only', which names a specific resource. However, it does not distinguish itself from the sibling tool 'get_player_props', which likely serves a very similar purpose. Without differentiation, an agent may struggle to choose between them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description advises to 'Prefer book/market/player filters' and mentions the default 'slim+limit' for payload size, but it does not provide guidance on when to use this tool versus alternatives like get_player_props or get_lines. There is no mention of conditions that make this tool the right choice or exclusions for other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.