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Lumify Sports Intelligence

get_odds_history

Read-onlyIdempotent

Get line-movement history for an event: a list of past odds snapshots (movements), each with its own timestamp, up to limit entries. bookmaker defaults to pinnacle. Use get_odds instead if you only need the current line.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax line-movement entries to return. Default 50.
event_idYesEvent id, from list_events, query_events, or search results.
bookmakerNoBookmaker slug. Defaults to pinnacle. Valid: pinnacle, fanduel, draftkings, betmgm, caesars, bet365, circa, hardrock, betonline, all, or a comma-separated list.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalNo
event_idNo
movementsNoOdds snapshots over time; each entry carries its own timestamp.

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds that it returns a list of past snapshots with timestamps and limit entries, but this doesn't go beyond the schema or output schema. It adds some context but not rich behavioral details.

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?

Two sentences, front-loaded with the core purpose, and every word earns its place. No fluff or redundant explanation.

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 read-only history tool with an output schema and well-documented params, the description is complete. It clearly distinguishes from get_odds and gives the key default behavior, making it fully sufficient for an agent to select and call it.

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 description coverage is 100%, with each parameter already documented (limit, event_id, bookmaker). The description echoes 'bookmaker defaults to pinnacle' and 'up to limit entries', but adds little meaning beyond what the schema provides. Baseline 3 is appropriate.

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's purpose: 'Get line-movement history for an event' and differentiates it from the sibling tool get_odds by noting the latter is for the current line. The verb 'Get' and resource 'line-movement history' are specific and unambiguous.

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

Usage Guidelines5/5

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

Provides explicit guidance on when to use this tool vs. the alternative: 'Use get_odds instead if you only need the current line.' Also notes the default bookmaker, giving practical context for invocation.

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

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct data resource or operation: events, live scores, odds, odds history, splits, stats, intelligence, player props, players, teams, sports, and seasons. Pairs like list_events vs query_events and get_event vs get_live_score are clearly differentiated by structured vs natural-language filtering and lightweight vs full detail.

Naming Consistency5/5

Tool names consistently follow a verb_noun snake_case pattern: get_*, list_*, search_*, query_*, batch_get_*, and estimate_cost. The naming conventions make the resource family immediately obvious, and deviations like batch_get_events are still predictable variants.

Tool Count4/5

19 tools is on the higher side, but each tool covers a specific sports-intelligence data product or workflow with little redundancy. The count feels intentional for the breadth of the domain rather than bloated.

Completeness4/5

The surface covers event discovery and retrieval, live scores, odds and line movement, splits, statistics, player props, intelligence, player/team/sport/season lookups, batch fetching, and cost estimation. Minor gaps like team standings or full rosters are not exposed, but core agent workflows are well supported.