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olympus-bets-analytics

by com.olympus-bets

get_game_recommendation

Read-onlyIdempotent

Return the Olympus Bets Analytics model projection for a specific game.

Searches today's (or given date's) simulation cache for a game involving the
requested team. Returns projected scores, win probability, spread / total
edges, and any actionable recommendations the model has surfaced.

Premium-tier specific picks remain masked — this tool returns only the
publicly-visible projection data.

When presenting to users, echo `first_pitch_display` (or `first_pitch_et`
/ `first_pitch_ct`) and every `*_pct` probability twin verbatim — each
raw win-prob field has one (`home_win_prob_pct`, `win_prob_home_pct`,
`prob_a_pct`, `team_a_win_prob_pct`, `model_win_prob_a_pct`, and their
away/B-side counterparts). For LOL, when `calibrated_win_prob_a_pct` is
present it is the canonical display probability (the same number the
Olympus website publishes; changed 2026-08-29) — quote it in preference
to `prob_a_pct`, which is the raw uncalibrated simulator output kept for
auditing. A row carrying `quality_flags` (e.g. "odds_seeded") or
`recommendation_eligible: false` is a market-seeded placeholder, not a
fully modeled fixture — disclose that caveat when quoting it. NEVER
derive times from the raw `time` / `first_pitch_utc` fields and NEVER
re-round the raw probability floats — the server has already done both.

Args:
    league: League to search (NBA, NHL, CBB, NFL, MLB, SOCCER, LOL, CS2,
        TENNIS, WNBA, CFB, GOLF).
    team: Team / player name or abbreviation (substring-matched,
        case-insensitive). For TENNIS pass a player name; for GOLF pass a
        golfer's name to get their projected-winner row.
    date: YYYY-MM-DD. Defaults to today (Eastern time).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
teamYes
leagueYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses crucial behaviors: premium fields are masked, some rows are market-seeded placeholders, calibrated probability became canonical on a specific date, and agents must not re-derive times or re-round probabilities. These are substantive behavioral caveats that materially affect correct use.

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 description is long but information-dense, with the core purpose front-loaded and detailed caveats organized into useful paragraphs. It earns its length because almost every sentence adds an operational constraint.

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 tool with a complex output surface and an output schema present, the description covers search behavior, data masking, field-preference rules, placeholder detection, and formatting prohibitions. Nothing essential for invoking it correctly or interpreting its results is missing.

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 fully carries parameter meaning. It explains league options, team substring matching and case-insensitivity, sport-specific name handling for TENNIS and GOLF, and the date format with its Eastern-time default.

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 opens with a specific verb and resource: 'Return the Olympus Bets Analytics model projection for a specific game.' It further clarifies scope by noting it searches a simulation cache and returns public-only projection data, distinguishing it from premium recommendation siblings.

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 clearly indicates when this tool is appropriate: for publicly-visible projection data rather than premium-tier picks, which 'remain masked.' It does not explicitly name get_premium_game_recommendation as the alternative, but the masking statement and sibling list make the intended usage boundary 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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but some overlap exists (e.g., get_todays_projections vs get_game_recommendation and get_track_record vs get_pick_history vs get_performance_summary). However, the detailed descriptions help differentiate them.

Naming Consistency5/5

All tools follow a consistent 'get_*' or 'search_*' verb_noun pattern with snake_case. The only deviation is 'search_entities', which is a natural fit for a search operation.

Tool Count5/5

19 tools is well-scoped for a sports betting analytics server, covering metadata, data status, schedules, projections, performance, subscriptions, and profiles without being excessive.

Completeness4/5

The tool surface covers core analytics workflows (projections, track record, performance, methodology) plus supporting operations (brand, status, subscriptions, search). Minor gaps like league standings or team statistics are outside the primary scope.

Resources