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alphapipeline

prediction.neg_risk_arbitrage

Read-only

Detect basket arbitrage in a Polymarket neg-risk (mutually-exclusive, multi-outcome) event - a full YES basket across all outcomes always settles to exactly $1, so a basket price away from $1 (after costs) is a near risk-free edge. Also returns buy/sell_basket_capacity_shares, the actual liquidity-bottleneck size executable right now, so this isn't just a top-of-book mirage. Polymarket only. Do not use for binary Yes/No markets (no basket to arbitrage) or for Kalshi (its Data ToS forbids this use). Paid in USDC on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_slugYesPolymarket event slug, from the event's URL on polymarket.com.
max_slippage_pctNoHow far past each leg's best price to walk the book when sizing capacity. Defaults to 1.0.
min_net_edge_pctNoMinimum net edge (%) required to flag arbitrage_viable: true. Defaults to 1.0.
assumed_round_trip_cost_pctNoGas + fees + slippage buffer, as a percentage of $1 basket notional. Defaults to 1.5.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noticeNo
event_slugYes
data_sourceYes
opportunityYes
generated_atYes
num_outcomesYes
basket_ask_sumNo
basket_bid_sumNo
arbitrage_viableYes
buy_basket_net_edge_usdNo
sell_basket_net_edge_usdNo
buy_basket_gross_edge_usdNo
buy_basket_capacity_sharesYes
sell_basket_gross_edge_usdNo
assumed_round_trip_cost_pctYes
sell_basket_capacity_sharesYes
buy_basket_capacity_notional_usdNo
sell_basket_capacity_notional_usdNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already establish read-only and non-destructive behavior, and the description adds substantial context beyond that: it returns executable basket capacity rather than just top-of-book, accounts for costs, and notes settlement in USDC on Base. It also explains the risk-free-edge mechanic without overpromising, saying 'near risk-free'.

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 dense but every sentence earns its place: it states what the tool does, why the edge exists, what the returned capacity means, which markets are excluded, and where settlement occurs. It is front-loaded with the core purpose and contains no filler.

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 output schema exists and annotations cover the read-only safety profile, the description is complete for an agent to select and invoke the tool correctly. It covers scope, exclusions, the core arbitrage logic, output semantics (capacity size, not a mirage), cost assumptions, and settlement environment.

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%, and all four parameters have clear descriptions in the input schema. The tool description adds high-level context ('after costs', 'liquidity-bottleneck size') but no parameter-level detail beyond what the schema already provides, so the baseline score of 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?

The description states a specific verb and resource: it detects basket arbitrage in Polymarket neg-risk events, and explains the underlying pricing condition (a full YES basket settling to $1). It clearly differentiates the tool from generic prediction-market tools by restricting it to mutually-exclusive multi-outcome events and explicitly excluding binary markets and Kalshi.

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 gives strong when-to-use and when-not-to-use guidance: use it for Polymarket neg-risk events, do not use it for binary Yes/No markets or on Kalshi. However, it does not name a specific sibling alternative to route the agent to for those excluded cases, so it falls just short of full alternative guidance.

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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