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by io.github.pipeworx-io

Polymarket Arbitrage

polymarket_arbitrage
Read-onlyIdempotent

Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a trending_scan of the top ~200 markets by weekly volume; pass event for the strongest per-event partition_check, or topic for a themed cross-event scan. event (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). topic (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventNoSingle-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topicNoCross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Polymarket for related events and checks monotonicity across them.

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

The description goes well beyond the annotations (which already indicate readOnly, idempotent, openWorld). It details the internal logic: monotonicity violations, partition-sum checks, Jaccard similarity threshold (≥0.30), placeholder filtering, fill check against CLOB depth. It also describes the response structure and the conditions under which signals are null or untradeable. No contradiction with annotations.

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?

The description is relatively long but every sentence contributes meaning. It is well-structured with clear sections (modes, semantic anchor, partition filter, response, fill check). It is front-loaded with the purpose and mode options. Could potentially be slightly more concise, but the density of useful information justifies the length.

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 complexity of the tool (multiple modes, multiple checks, edge cases) and the absence of an output schema, the description is remarkably complete. It explains the return fields, the fill check outcome, the placeholder filter, and when signals are null. It also covers the semantic anchor and the conditions for cross-event pairing. No additional context seems missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already has detailed descriptions for event and topic. The description adds value by providing concrete examples (e.g., 'fed-decision-may-2026', 'Strait of Hormuz traffic returns to normal'), clarifying that no args triggers a trending scan, and giving usage recommendations. However, the schema descriptions are already quite strong, so the extra value is moderate.

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 clearly states the tool's core function: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It immediately distinguishes three modes (trending, event, topic) and explains what each does. It implicitly distinguishes from sibling tools like polymarket_edges by focusing on arbitrage rather than general edges.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells the user when to use each mode: 'Call with NO args for a trending_scan... pass event for the strongest per-event partition_check, or topic for a themed cross-event scan.' It recommends event mode for specific markets, explains cross-event mode catches patterns, and advises against trading when realizable_edge_pp ≤ 0. It also references the sibling tool polymarket_fill_risk for custom sizing.

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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TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with a few overlapping pairs (e.g., ask_pipeworx vs ask_pipeworx_grounded, multiple polymarket tools) that could cause mild confusion, but descriptions adequately differentiate them.

Naming Consistency3/5

Tool names consistently use snake_case, but the verb_noun pattern is not consistently applied; some names are noun_noun (dallas_datasets, bet_research) or adjective_noun (ai_visibility_check), creating a mixed nomenclature.

Tool Count2/5

With 33 tools, the server exceeds the typical well-scoped range. While the broad data domain justifies many tools, the count feels heavy and would benefit from consolidation of related functions.

Completeness4/5

The tool set covers a wide array of domains (company data, drugs, economics, prediction markets, memory, subscriptions) with only minor gaps (e.g., no direct web search tool, as ask_pipeworx mostly covers it). Overall, it is comprehensive for its purpose.

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