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predictionmarketspicks

PredictionMarketsPicks Quant

Official

Calculate EV Edge

calculate_ev
Read-only

Compute expected-value edge on prediction market contracts. Input market price and your probability estimate to get edge percentage and a clear action signal.

Instructions

Calculate the expected-value edge on a Kalshi or Polymarket prediction-market contract. Given the current market price (in cents, i.e. the implied probability) and your own probability estimate, returns the % edge and a BUY / SELL / SKIP signal with a plain-English read. Use for "is this contract mispriced", "what is my edge", "should I take this position".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketPriceYesCurrent contract price in cents (1–99), equal to the implied probability in %.
yourProbabilityYesYour own estimate of the true probability the contract resolves YES, in % (0–100).
Behavior4/5

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

Annotations already declare readOnlyHint=true (non-destructive), and the description adds that the tool returns '% edge' and a 'BUY / SELL / SKIP signal with a plain-English read', disclosing output behavior beyond structured fields.

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 main action and platforms, then output description. No wasted words.

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 simple calculation tool with two numeric parameters and no output schema, the description covers purpose, inputs, and outputs adequately. No gaps.

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 coverage is 100% with clear parameter descriptions. The description does not add further semantic detail beyond what's in the schema, so 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?

Description uses specific verbs ('calculate', 'returns') and resources ('Kalshi or Polymarket prediction-market contract'), clearly distinguishing from sibling tools like 'combo_edge' or 'kelly_size' which compute different metrics.

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?

Explicitly lists use cases: 'is this contract mispriced', 'what is my edge', 'should I take this position'. However, it does not mention when not to use it or suggest alternatives, which would make it 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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