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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. 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 declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description adds substantial behavioral detail beyond that: the 3pp threshold for partition signals, the Jaccard similarity anchor for cross-event pairs, placeholder filtering with >20% threshold, and the fill check against live CLOB depth with explicit trading advice. This is a rich behavioral disclosure.

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 long but well-structured with clear section labels (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK). It front-loads the purpose and call modes. Some redundancy exists (e.g., the fill check is described twice), but every major section adds operational context. It is dense yet organized.

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?

The tool is complex with no output schema, but the description thoroughly covers the response shape (opportunities[], partition_check fields), edge cases (placeholders, low similarity), and the critical fill-check behavior. It even references a sibling for custom sizing. This is a complete standalone description for an agent to correctly invoke the tool.

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% and both parameters have descriptions, but the tool description elevates semantics by explaining the two modes in depth. It gives concrete examples of event slugs and topic seed questions, explains how the tool behaves differently in each mode, and clarifies when to prefer one over the other. This goes well beyond what the schema entries provide.

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 opens with a specific verb+resource: "Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks." It clearly distinguishes this from siblings like polymarket_edges and polymarket_fill_risk by focusing on arbitrage detection and listing the three calling modes.

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 is given for when to use each mode: "Call with NO args for a trending_scan... pass event... or topic..." It recommends event for a known market and explains when cross-event scan is better. It also names an alternative sibling: "For custom sizing use polymarket_fill_risk." This gives clear when-to-use and when-not-to-use context.

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

A3.6/5.0
Disambiguation2/5

There is heavy overlap in the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research, validate_claim) — several are near-identical 'route a natural-language question to a source' tools differing only by small qualifiers. ai_visibility_check vs scan_competitor_ai_presence and entity_profile vs compare_entities vs recent_changes also blur together. An agent could easily misselect among these.

Naming Consistency4/5

The dominant convention is snake_case verb_noun/noun_verb (list_subscriptions, scan_dependency, validate_claim, resolve_entity) which is fairly consistent, but there are several bare single-word verbs (lookup, sequence, variation, vep, xrefs, recall, remember, forget) that break the pattern. No camelCase is present, so the inconsistency is minor rather than chaotic.

Tool Count2/5

38 tools is heavy, and the overwhelming majority (~31) are Pipeworx meta-tools (subscriptions, memory, feedback, trend, discovery, llms.txt generation) that have nothing to do with the server's declared Ensembl identity. Only about 7 tools are actually genomics-related, so the count is inflated by off-domain additions that dilute the surface.

Completeness2/5

For the Ensembl domain, the surface covers gene lookup, symbol resolution, sequence retrieval, orthologs, SNPs, variant effect prediction, and xrefs — but misses major Ensembl capabilities like gene trees/families, regulatory features, comparative/multi-species alignments, expression data, phenotypes, GO/ontology annotations, and region/overlap queries. Conversely the Pipeworx tools are complete for their own domain but irrelevant here, leaving the declared domain notably incomplete.

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