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olympus-bets-analytics

by com.olympus-bets
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get_todays_projections

Read-onlyIdempotent

Return today's free sports betting projections published by Olympus Bets Analytics.

Each projection includes the matchup, market (spread/moneyline/total), the
line, the American odds at publication, the calibrated model probability, the
edge versus the market, the confidence tier, key
factors, and a short writeup.

These are PUBLIC projections — the same set published on
https://app.olympus-bets.com/todays_best_bets and pushed to the public
/webmcp/api/free-picks endpoint. Premium tier projections are not exposed
here.

Args:
    league: Optional league filter (e.g. "NBA", "NHL", "MLB", "CBB", "NFL",
        "SOCCER", "LOL", "GOLF"). Omit to return all leagues.
    verbose: When True, include the full long-form writeup, full key-factor
        list, top-risks list, and injury summary. Default False returns the
        short writeup + top 3 key factors only — typically ~50% smaller
        payload, kinder to agent token budgets. Set verbose=True when an
        agent specifically wants the detail (e.g., user asked "explain this
        pick").

Returns:
    ``{date, total, leagues_active, projections: [...]}``

Input Schema

NameRequiredDescriptionDefault
leagueNo
verboseNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "get_todays_projectionsDictOutput",
+  "type": "object"
+}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already establish readOnly/idempotent/openWorld, so the bar is lower. The description adds real context on top: these are PUBLIC projections sourced from a specific published endpoint, premium projections are deliberately excluded, and verbose toggles payload size (~50% smaller default). It does not discuss auth or rate limits, keeping it from a 5.

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?

Front-loaded with purpose and content, then args and returns; every section is useful. The explicit Returns block is mildly redundant given an output schema exists, but it is short and the overall structure is clean.

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?

For a two-param read tool with an output schema and safety annotations, nothing material is missing: scope (public vs premium), data shape, parameter semantics, and the token-budget tradeoff are all covered.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden and does so well: league enumerates valid values (NBA, NHL, MLB, CBB, NFL, SOCCER, LOL, GOLF) and states the omit-to-get-all default, while verbose explains exactly what extra fields it adds and when to enable it.

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 names a specific verb and resource ('Return today's free sports betting projections') and immediately enumerates what each projection contains (matchup, market, line, odds, probability, edge, confidence tier, factors, writeup). It also distinguishes scope from a premium tier, so the agent knows exactly what it is getting.

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 clear context for both parameters — omit league to get all leagues, set verbose=True when the user wants the detail (e.g. 'explain this pick'). It does not name sibling alternatives (e.g. get_premium_slate for premium picks), so it falls short of explicit when-not guidance, but usage is unambiguous.

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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