infersports

Compare External Probability

compare_prob

Read-only

Judge an external probability (e.g. a Polymarket/Kalshi price) against our sharp fair line — ONE call.

Resolves the fixture, de-vigs the sharp book to a fair probability (power de-vig for 3-way 1x2),
and reports the edge ``fair_prob − external_prob`` in percentage points, the ROI, and a verdict
(good / marginal / no_edge). DETECTION ONLY: InferSports never ingests prediction-market data,
sizes a stake, or picks — it gives you the sharp reference and the gap; the call is yours.

Args:
    query: natural-language fixture, e.g. "France vs Argentina" or a single team.
    external_prob: the external implied probability for ``outcome``, in (0,1). Pre-net it for the
        venue's fee/spread (e.g. a Polymarket YES ask of 0.55 → 0.55).
    market_type: "1x2" (default; the prediction-market-comparable moneyline), "asian_handicap"
        (only ±0.5 maps cleanly to a binary), or "totals".
    period: "full_time" (default) or "half_time".
    outcome: which leg the probability is for — home/draw/away (1x2), home/away (AH), over/under.
    external_label: optional source label echoed back, e.g. "polymarket" | "kalshi".
    sport: optional filter — "football" or "basketball".
    date: optional UTC date "YYYY-MM-DD" to disambiguate same-name fixtures.

Read ``caveats`` before acting: a 1x2 fair is regulation 90-min (a prediction market that includes
extra time / "to advance" is a different market); quarter/integer AH carries push mass. On an
ambiguous query ``status`` is "ambiguous" — do not guess. ``status`` is "no_line" when no sharp
fair is available to judge against.

Input Schema

TableJSON Schema

Name	Required	Default
`date`	No
`query`	Yes
`sport`	No
`period`	No	full_time
`outcome`	No	home
`market_type`	No	1x2
`external_prob`	Yes
`external_label`	No

TDQS

A4.8/5.0

Behavior5/5

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

The description aligns with the annotations' readOnlyHint by stating it never ingests data, sizes stakes, or picks – it only reports the gap. It details the process (resolve, de-vig, report edge/ROI/verdict) and caveats about market types, fully disclosing behavior.

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?

The description is efficiently structured: a clear one-line summary, followed by detailed behavior, parameter list, and caveats. Each sentence adds value without redundancy, and it is front-loaded with the core purpose.

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 (8 params, no output schema), the description provides ample context: it explains the output fields (edge, ROI, verdict), potential statuses (ambiguous, no_line), and market-specific caveats. This allows an agent to understand the full lifecycle of a call.

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 coverage, the description explains all 8 parameters in the 'Args' section with examples, defaults, and nuances (e.g., external_prob pre-net, market_type limitations). This adds significant meaning beyond the bare schema.

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 explicitly states the tool judges an external probability against a sharp fair line, using verbs like 'judge' and 'compare'. It distinguishes from siblings by emphasizing 'DETECTION ONLY' and contrasting with tools that might ingest or act on data.

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 provides examples, explains when to use (e.g., for comparing external probabilities), and includes caveats about market types and ambiguous queries. However, it does not explicitly contrast with sibling tools like 'compare_lines' or 'find_value', leaving some ambiguity about which tool to choose in specific scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All infersports tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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

Need Help?