infersports

Find Arbitrage

find_arbitrage

Read-only

Find cross-book arbitrage in a fixture — a guaranteed-profit price split — in ONE call.

Resolves the fixture, then for each market/line takes the best price per outcome across books;
when the inverse prices sum to < 1 there is a locked margin regardless of result. Reports the
margin % and which book holds each leg (legs must come from ≥2 distinct books). DETECTION ONLY:
no stake sizing, no bet links — InferSports is read-only.

Args:
    query: natural-language fixture, e.g. "Netherlands vs Algeria" or a single team.
    markets: optional filter — any of "1x2", "asian_handicap", "totals" (default: all).
    period: optional — "full_time" or "half_time" (default: both).
    min_margin_pct: only report opportunities with at least this guaranteed margin (default 0).
    format: odds format — decimal | hk | malay | american | indonesian | probability.
    sport: optional filter — "football" or "basketball".
    date: optional UTC date "YYYY-MM-DD" to disambiguate same-name fixtures.

On an ambiguous query, ``status`` is "ambiguous" and ``ask_user`` carries a prompt — do not guess.

Input Schema

TableJSON Schema

Name	Required	Default
`date`	No
`query`	Yes
`sport`	No
`format`	No	decimal
`period`	No
`markets`	No
`min_margin_pct`	No

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the readOnlyHint annotation, the description adds that it is read-only ('InferSports is read-only'), detection-only, and explains the arbitrage calculation logic and the requirement for legs from distinct books.

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 efficiently structured with a purpose paragraph, parameter list, and ambiguous query note. It is detailed but every sentence adds value, though slightly lengthy.

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?

Given the tool's complexity and lack of output schema, the description explains the return values (margin %, legs, distinct books) and error handling (ambiguous queries), making it complete for agent use.

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?

Despite 0% schema description coverage, the description provides a detailed Args section for all 7 parameters, including defaults, possible values, and natural language examples, fully compensating for the schema gap.

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 it finds cross-book arbitrage in a fixture, using a verb ('find') and specific resource ('arbitrage in a fixture'). It distinguishes from siblings like 'find_value' or 'scan_slate' by focusing solely on guaranteed-profit price splits.

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 notes it is 'DETECTION ONLY' and handles ambiguous queries with an 'ask_user' prompt. It does not explicitly compare to alternatives, but the context makes its use case 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

A4.6/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: compare_lines contrasts bookmakers, compare_prob evaluates external probabilities, find_arbitrage detects arbitrage opportunities, find_match resolves fixtures, etc. Even related tools like get_sharp_line (one-call line) and compare_lines (event_id-based comparison) are complementary rather than overlapping. No ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., compare_lines, find_match, list_bookmakers). Verbs like compare, find, get, list, scan, score are uniform. No mixing of conventions or vague names.

Tool Count5/5

With 17 tools covering fixture discovery, odds retrieval, comparisons, value/arb detection, line movement, results, and slate scanning, the count is well-scoped for a sports betting odds API. No unnecessary tools, and the set feels complete without being bloated.

Completeness5/5

The tool surface covers the full lifecycle: find matches (find_match, list_events, list_today_matches), get odds (get_match_odds, get_sharp_line, compare_lines), detect value/arb (find_value, find_arbitrage, scan_slate), analyze lines (get_opening_line, explain_handicap, score_prob), and retrieve results (get_result, list_results). No obvious gaps for the stated read-only odds analysis domain.

Resources

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