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Khavel

NBA Prop Lab MCP Server

by Khavel

Get Backtest Summary

proplab_backtest_summary
Read-onlyIdempotent

Aggregate backtest results for PREMIUM (Good+) props only: total picks, hits, misses, pushes, hit rate, profit, and ROI over a date range, with an optional league filter.

Instructions

Aggregate backtest over PREMIUM (Good+) picks only: total picks, hits, misses, pushes, hit rate, profit, and ROI for a date range. Requires auth (PROPLAB_API_KEY). Supports league filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD (default: today)
fromNoStart date YYYY-MM-DD (default: 14 days ago)
leagueNoFilter by league

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral context the annotations do not: it requires auth via PROPLAB_API_KEY, and it restricts results to PREMIUM (Good+) picks rather than all picks. It does not discuss defaults or rate limits, but the additions are substantive.

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

Conciseness5/5

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

Two sentences with no filler: the scope and returned metrics come first, then the auth and filter constraints. Every clause carries information an agent needs, especially given there is no output schema.

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

Completeness4/5

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

With no output schema, the description usefully enumerates the metrics returned (picks, hits, misses, pushes, hit rate, profit, ROI), and it discloses the auth requirement and PREMIUM-only scope. The main omission is that defaults for from/to live only in the schema, but overall an agent has enough to call it correctly.

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 description coverage is 100% with per-parameter descriptions and an enum for league, so the schema already carries parameter meaning. The description only restates 'for a date range' and 'Supports league filter', adding no syntax or default information beyond the schema. Baseline 3 applies.

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 names a specific operation (aggregate backtest) and a precise scope: 'PREMIUM (Good+) picks only', which separates it from the rating/stat/daily breakdown siblings. It also enumerates the returned metrics, so an agent knows exactly what this tool produces. It stops short of naming a sibling as the alternative, so it is clear but not fully differentiated.

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?

'OVER PREMIUM (Good+) picks only' and 'Supports league filter' imply when the tool applies, but there is no explicit statement of when to choose this over proplab_backtest_daily, proplab_backtest_by_rating, or proplab_backtest_by_stat. Usage is inferable from the aggregation scope rather than stated.

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