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PropLine — Sports Betting Odds & Prop Resolution

Get event stats

propline_get_event_stats
Read-onlyIdempotent

Book-agnostic raw box-score stats for an event. Returns per-player stats (e.g. strikeouts, hits, points, rebounds, shots-on-goal) decoupled from any sportsbook's lines. LIVE during games for major US sports (MLB + WNBA now; NFL, NCAAF, NBA, NHL at season start): while the event's status is in_progress, stats refresh ~every 90 seconds with cumulative in-game values — use this to answer 'how is this prop tracking right now'. Treat in-progress numbers as partial; at status=final they are the official box score. Other sports populate stats at game completion. Free tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_idYes
sport_keyYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark the tool as read-only, but the description adds substantial behavioral detail: stats refresh ~every 90 seconds during live games, in-progress numbers are partial, final status means official box score, and other sports populate at completion. This goes far beyond the annotation hints and gives the agent accurate expectations about data freshness and reliability.

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?

The description is dense but every sentence contributes: purpose, content, live refresh, partial-data caveat, coverage across sports, and free tier. It is front-loaded with the core purpose and avoids fluff.

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?

Despite having no output schema, the description gives a clear picture of what to expect (per-player stats, live vs final, refresh cadence). For a simple two-parameter read-only tool, the description is sufficiently complete for an agent to invoke it correctly and interpret results appropriately.

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 coverage is 0% and the description does not explain the 'sport_key' or 'event_id' parameters. It mentions sports by name (MLB, WNBA) but never maps them to the required parameters, leaving the agent to guess acceptable values. The description adds no direct parameter meaning.

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

Purpose5/5

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

The description clearly states the tool returns 'book-agnostic raw box-score stats for an event' with specific examples (strikeouts, hits, points). It distinguishes itself from sportsbook-line tools by emphasizing the stats are 'decoupled from any sportsbook's lines', making the purpose unambiguous.

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?

The description provides explicit context on when to use the tool: 'use this to answer how is this prop tracking right now' and explains live behavior during games. It does not name alternative sibling tools or provide explicit when-not-to-use guidance, but the targeted use case is clear.

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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TDQS

A4.1/5.0
Disambiguation3/5

The tools are mostly distinct by purpose, but several overlap in areas like odds retrieval (get_odds vs get_best_line vs get_event_ev) and historical data (get_odds_history vs get_odds_closing vs export_odds_history). Descriptions are detailed and clarify distinctions, but the close functional relationships (e.g., get_event_movement vs get_odds_history) may cause selection ambiguity for an agent.

Naming Consistency4/5

The naming pattern is largely consistent: propline_<verb>_<noun> with verbs like get, list, export. Most tools follow this structure (e.g., get_event_results, list_events, list_sports). Deviations include 'propline_export_odds_history' (export instead of get) and a few longer names like 'propline_get_mlb_grand_salami' and 'propline_get_nhl_daily_goals_total' that break the simple verb_noun pattern but are still readable. Overall, the naming is predictable with minor exceptions.

Tool Count4/5

With 23 tools for a sports betting odds and prop resolution server, the count is on the higher side but still within a reasonable range given the domain's complexity (odds, EV, movement, results, player trends, webhooks, exports). Each tool serves a distinct function, though some could be consolidated (e.g., grand salami and NHL daily totals could be one). Slightly heavy but not excessive.

Completeness4/5

The tool set covers the core lifecycle: discover sports and events (list_sports, list_events), retrieve odds and markets (get_odds, list_event_markets), analyze EV and lines (get_event_ev, get_best_line, get_event_movement), track results and player stats (get_event_results, get_event_stats, get_player_history, get_player_trends), and backfill via exports. Missing features include webhook management (deliberately omitted) and possibly batch operations, but the surface is comprehensive for the stated purpose.