propline_list_event_marketsList the market types available for a specific event (e.g. h2h, spreads, totals, player_points, pitcher_strikeouts). Useful when you don't know which prop markets a given event carries.
| Name | Required | Description | Default |
|---|---|---|---|
| event_id | Yes | ||
| sport_key | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description need not repeat that. It adds contextual detail about return content (market types) but does not disclose pagination, output format, or whether results are dynamic. This is moderate added value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action and examples, plus a clear use-case clause. No redundancy or filler; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool, the description gives the purpose and when to use it, and annotations cover safety. However, the lack of parameter explanations and any output format description creates gaps that could confuse an agent, especially with two required fields lacking schema descriptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 only hints at 'specific event' but never explicitly explains event_id or sport_key, their formats, or why sport_key is needed. This leaves the agent guessing about required parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists market types for a specific event, with concrete examples (h2h, spreads, totals). The verb 'List' matches the title and it distinguishes itself from sibling tools like list_events and list_sports by focusing on per-event markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context: 'Useful when you don't know which prop markets a given event carries.' This clearly indicates when to use the tool, but it does not name alternatives or when-not-to-use scenarios, so it falls short of a full prescriptive set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.