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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. Changed1 schema field changed
    • removedInput schema / anyOf
      Removed value: -[
      -  {
      -    "required": [
      -      "event"
      -    ]
      -  },
      -  {
      -    "required": [
      -      "topic"
      -    ]
      -  }
      -]
  2. Changed3 schema fields changed
    • addedInput schema / anyOf
      Added value: +[
      +  {
      +    "required": [
      +      "event"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "topic"
      +    ]
      +  }
      +]
    • changedInput schema / properties / event / description
      Previous value: -"Single-event mode: Polymarket event slug (e.g. \"when-will-bitcoin-hit-150k\") or full URL."New value: +"Single-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."
    • changedInput schema / properties / topic / description
      Previous value: -"Cross-event mode: a topic or seed question. Tool searches Polymarket for related markets across separate events and checks monotonicity across them. E.g. \"Strait of Hormuz traffic returns to normal\"."New value: +"Cross-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."
  3. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. Description adds behavioral details: semantic anchor (Jaccard >=0.30), partition filter (placeholder fraction), fill check logic (theoretical vs realizable edge). 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?

Description is detailed and contains technical jargon, but it front-loads key information and uses clear sectioning. Slightly verbose but efficient for the complexity.

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?

No output schema, but the description explains the response structure (opportunities[] with fields, partition_check, fill check). Covers complex logic like Jaccard similarity, partition filter, and fill check comprehensively.

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?

Schema description coverage is 100% with brief descriptions. The tool description enriches each parameter with examples, expected formats, and detailed behavior per mode, adding significant 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 clearly states the tool's purpose: finding arbitrage opportunities via monotonicity violations and partition-sum checks. It explains the three modes (no args, event, topic) and distinguishes from sibling tools like polymarket_fill_risk and polymarket_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?

Explicit guidance on when to use each mode: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. Also warns when not to trade (realizable_edge <= 0) and references sibling tool 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

B3.2/5.0
Disambiguation1/5

The tool set is a chaotic mix of geographic routing, AI visibility, betting analysis, memory storage, and random utilities. Many tools overlap in purpose (e.g., multiple data lookup tools like ask_pipeworx, discover_tools, resolve_entity), and the domain is completely inconsistent, making it nearly impossible for an agent to distinguish which tool to use for a given task.

Naming Consistency1/5

Tool names follow no consistent pattern; they mix snake_case (ai_visibility_check, ask_pipeworx), camelCase (generate_llms_txt), and arbitrary verbs without a clear verb_noun structure. Some names are vague (processV2-like patterns are absent, but e.g., 'forget' is a single verb). This chaotic naming prevents an agent from predicting tool functions.

Tool Count1/5

With 27 tools covering routing, AI marketing, betting, memory, and more, the count is extremely mismatched for the server's implied purpose ('Openrouteservice'). Even ignoring the name, the number is high and the scope is far too broad, making the set unwieldy and unfocused.

Completeness1/5

No coherent domain can be inferred from the tool set; it is an arbitrary collection. The routing tools are present but overshadowed by unrelated tools. For any single domain (e.g., betting or routing), the surface is either incomplete or includes extraneous tools, leaving the set severely lacking a clear purpose.