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Keel Stats

Player Props Research, Model & Cheat Sheet (Pro)

props_research
Read-onlyIdempotent

Get Pro player props research: pass player_id for a player's upcoming lines, book-by-book odds & moves, line comparisons (averages, diffs, L5/L10/L20/Season hit rates, model probability), season over/under/push record vs closing lines, and alternate ladders; or omit player_id for today's prop board (with Keel model probability & market edge, optionally filtered by game_id) and the daily cheat sheet (line moves & DvP matchups).

Input Schema

NameRequiredDescriptionDefault
dateNoOptional date (YYYY-MM-DD) for the NBA daily prop board.
statNoOptional stat code for the daily board or book-by-book view (e.g. NBA: "pts", "reb", "ast", "tpm", "pra"; NFL: "passing_yards", "rushing_yards", "receiving_yards", "receptions").
leagueYesLeague ("nba" or "nfl").
game_idNoOptional numeric game ID to filter the daily prop board to a single game.
player_idNoOptional numeric player ID to inspect his upcoming lines, book-by-book odds, line comparisons, closing-line record, and ladders. Omit for the daily prop board and cheat sheet.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds substantive mode-dependent behavior: the two distinct result sets and the specific analytics each returns. With no output schema, this return-shape disclosure carries real weight; only rate limits, auth/Pro-entitlement requirements, and pagination are left unstated.

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 two-mode split is front-loaded and each clause maps to a real capability rather than filler. However, it is delivered as a single semicolon-chained run-on, which makes the branch structure harder to parse than two or three short sentences would.

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

Completeness5/5

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

With five optional-style parameters, no output schema, and a read-only profile already declared by annotations, the description supplies exactly the missing piece: what each mode returns. An agent can decide which mode to invoke and what to expect without further documentation.

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 baseline applies, and the description largely restates what the schema already documents for player_id, game_id, date, and stat. It does add that player_id selects the entire output mode, which is marginally useful, but no format or interaction detail goes beyond the schema.

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 verb and resource ('Get Pro player props research') and enumerates the concrete payload: book-by-book odds & moves, line comparisons, hit rates, model probability, closing-line records, alternate ladders, and a daily cheat sheet. That enumeration does implicitly separate it from siblings like game_projection or defense_vs_position, but no sibling is named, so it stops short of a 5.

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

Usage Guidelines4/5

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

It gives an explicit branch condition: pass player_id for per-player research, omit player_id for today's board plus cheat sheet, with an optional game_id filter. What is missing is when to prefer this over a sibling such as player_splits_and_on_off or game_projection, so it's clear context without exclusions.

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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