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Khavel

NBA Prop Lab MCP Server

by Khavel

Evaluate a Pick

proplab_evaluate_pick

Score a custom NBA or WNBA player-prop pick on demand through a 7-block model. Returns a 0-100 confidence score, rating, and block-by-block breakdown.

Instructions

Score a custom pick on-demand through PropLab's 7-block engine. Returns a confidence score (0-100), rating, and block-by-block breakdown. Requires auth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lineYesThe prop line, e.g. 25.5
statTypeYesStat market: Points, Rebounds, Assists, Threes, Steals, Blocks, PtsRebAst, PtsReb, PtsAst, RebAst
directionYesOver or Under
playerNameYesFull player name, e.g. 'LeBron James'
opponentTeamNoOpponent team abbreviation, e.g. 'LAL'. Auto-detected from today's schedule if omitted

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, and idempotentHint=false, so the agent knows this is a non-idempotent operation with external dependencies. The description adds that it 'Requires auth' and returns a confidence score and breakdown, but does not elaborate on rate limits, execution time, or side effects. This is adequate but not rich 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.

Conciseness4/5

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

The description is two concise sentences, front-loaded with the core action. Every sentence earns its place, though it could be slightly more structured by separating usage or return details. Not maximally efficient but close.

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

Completeness3/5

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

With no output schema, the description partially explains return values ('confidence score (0-100), rating, and block-by-block breakdown'), which is helpful. However, for a tool with five parameters and annotations that don't cover all behavioral aspects, it lacks details on authentication mechanics, error handling, or when the output might be unavailable. Adequate but with clear gaps.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all five parameters, including enums and examples. The description adds no parameter-specific meaning beyond what the schema provides, so baseline 3 is correct. No syntax or format details are added.

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

Purpose4/5

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

The description states a clear verb and resource: 'Score a custom pick on-demand through PropLab's 7-block engine.' It distinguishes this tool from sibling tools like proplab_pick_details because it processes a custom pick rather than fetching an existing pick's details. However, it could more explicitly differentiate from proplab_player_research or proplab_track_record, which also provide evaluations, leaving slight ambiguity for an agent choosing 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 Guidelines3/5

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

The phrase 'on-demand' implies usage context but does not explicitly state when to use this tool versus alternatives like proplab_pick_details. No exclusions or prerequisites beyond authentication are mentioned, leaving the agent to infer the appropriate scenario. This is minimum viable guidance.

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