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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. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark it as read-only, open-world, idempotent, non-destructive. Description adds extensive behavioral details: partition filter with placeholder fraction, semantic anchor with Jaccard similarity, fill check against CLOB depth, and response structure. No contradictions.

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 thorough but somewhat verbose. It is well-structured with clear sections for each mode and additional technical notes (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK). Every sentence adds value, but it could be slightly more concise.

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 no output schema, the description summarizes the response format (opportunities[], partition_check) and explains edge cases (fill check, placeholder filters). It also references a sibling tool (polymarket_fill_risk) for custom sizing. Very complete.

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 coverage is 100%. Description adds significant meaning beyond the schema: explains that 'event' accepts slugs or URLs, 'topic' searches related events, and provides examples. Also clarifies the behavior of each mode in detail.

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 explicitly states the tool finds arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It clearly distinguishes three modes (trending_scan, event, topic) with specific examples and use cases, making the purpose unmistakable.

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?

Provides explicit guidance on when to use each parameter: 'no args for trending scan', 'event for specific market', 'topic for cross-event scanning'. Also explains why cross-event mode is better for certain patterns. Implicitly tells when not to use alternatives.

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

A3.8/5.0
Disambiguation3/5

Most tools understandably fall into distinct clusters (BLS data, Polymarket, entity research, memory, subscriptions) and have detailed descriptions, but there is real overlap among the query entry points: ask_pipeworx and ask_pipeworx_beta are currently identical, and ask_pipeworx, deep_research, and validate_claim can all answer similar factual questions. The descriptions help an agent choose, but the set still contains more than a couple of near-duplicate paths.

Naming Consistency3/5

All names are lowercase snake_case and several clusters share domain prefixes like bls_, polymarket_, and pipeworx_, which keeps the surface readable. However, the semantic naming pattern is mixed: verb+noun names like resolve_entity and list_subscriptions coexist with noun phrases like entity_profile, recent_alerts, and bls_latest, plus brand-led names like ask_pipeworx and polymarket_edges.

Tool Count2/5

At 36 tools, the set is well past the 25+ threshold for a heavy tool surface, and several tools inflate the count: duplicate ask_pipeworx variants, multiple overlapping Polymarket scanners, and one-off meta helpers. The broad Pipeworx scope explains some of the breadth, but the redundancy makes the set feel bloated.

Completeness4/5

The set covers its core workflows well: data lookup, grounded verification, entity profiling and comparison, BLS series access, Polymarket research, subscriptions, memory, and feedback. Minor gaps remain, such as no subscription-editing tool, no dedicated citation-reader tool, and no general web-search tool, but ask_pipeworx acts as a catch-all router that lets agents work around most of them.