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Combo Edge Verdict

combo_edge
Read-only

Grade a same-game combo quote against fair value using leg prices and true win probability. Get expected value, correlation trap flag, and verdict from SMASH to RUN.

Instructions

Grade a same-game combo (parlay-style multi-leg position) on a prediction market against its fair value. Given each leg price in cents and your correlation-aware estimate of the true joint win probability, returns the fair-value ODDS BAND to grade a quote against. Pass offeredOdds — the price your platform actually quotes for the combo (Kalshi combo RFQ or an SGP product) — to get the expected-value %, a negative-correlation-trap flag, and a 7-tier verdict (SMASH / PLAY / LEAN / RISK / NO_VALUE / PASS / RUN). Without offeredOdds it returns fair value + band only (no verdict) — never grade EV off the product of the leg prices, which no venue pays. Use for "is this combo worth it", "grade my parlay quote", "same-game combo value".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
legPricesYesEach leg's YES price in cents (1–99). Used only for the theoretical assemble ceiling.
offeredOddsNoThe combo price your platform actually quotes — American odds (e.g. -150, 988) or a decimal payout multiplier (e.g. 10.7). Grades EV + verdict against fair value. Omit to get fair value + band only.
trueWinProbabilityYesYour correlation-aware estimate of the true joint probability all legs hit, in % (0–100).
Behavior5/5

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

Annotations already indicate read-only and non-open-world; descriptions add rich behavioral context: returns fair-value ODDS BAND, EV% with/without offeredOdds, a negative-correlation-trap flag, and a 7-tier verdict. No contradiction.

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?

Front-loaded with main purpose, but includes redundant warning about product of leg prices. Slightly verbose but efficient given complexity; every sentence adds info.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers main outputs and parameter behavior well, but lacks numeric ranges for ODDS BAND or definitions of each verdict level. Adequate for an AI agent without output schema.

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 covers 100% of parameters, but description adds meaning: legPrices 'used only for theoretical assemble ceiling', offeredOdds format and effect, trueWinProbability as correlation-aware estimate. Adds value beyond 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 begins with a specific verb-resource pair ('Grade a same-game combo... against its fair value'), clearly defines inputs and outputs, and differentiates from siblings like calculate_ev by emphasizing same-game combo valuation and avoiding simple product calculation.

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?

Provides explicit use cases ('is this combo worth it', 'grade my parlay quote') and warns against misusing the product of leg prices. Lacks direct comparison to sibling tools but implies specificity to same-game combos.

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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