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

Schema Changelog

Changes observed during successful MCP inspections.

AddedJun 9, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Despite readOnlyHint already conveying non-mutation, the description goes well beyond annotations: it discloses the de-vig computation, output fields (edge, ROI, verdict), status values ambiguous and no_line, and market caveats like 90-minute vs extra-time. No contradiction with the annotations.

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 long but deliberately structured: purpose first, then Args, then caveats. It front-loads the core action and detection-only nature, and every paragraph adds operational information rather than repeating the schema or annotations.

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?

With 8 parameters, no output schema, and 0% schema description coverage, this context is hard to make complete. The description documents all params, specifies valid values and defaults, lists computed fields, and warns about ambiguity, no_line, and market-shape edge cases.

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?

The input schema has 0% description coverage, so the description carries the full burden. The Args section explains every parameter with valid values, defaults, and examples, fully compensating for 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?

Opens with a specific verb ('Judge ... against our sharp fair line') and a resource (external probability vs sharp fair line), and adds the unambiguous scope 'ONE call'. The detection-only clarification further separates it from scoring or betting tools in the sibling list.

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?

Gives clear context: use it when you have an external prediction-market probability and need the fair-line gap, and it explicitly says it never sizes stakes or picks. It stops short of naming sibling alternatives such as compare_lines or score_prob, so it earns a 4 rather than a 5.

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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