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Wynncraft

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. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and destructiveHint, so the agent knows it's safe. The description adds rich behavioral context: explains monotonicity checks, partition-sum checks, semantic anchor (Jaccard ≥0.30), partition filter (placeholder slugs >20% yield null), and fill check against CLOB depth with realizable_edge_pp ≤ 0 meaning no trade. No contradictions 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 well-structured (one-liner followed by mode breakdown, then technical details), but it is quite long. Some specifics like threshold 0.30 and placeholder fraction details could be condensed. However, the structure is logical and front-loaded, making it still effective for an AI agent.

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 description is extremely complete given the tool's complexity. It covers all parameters, explains three usage modes, details algorithmic checks, describes the response structure (opportunities[], partition_check, fill check output), and even warns about realizable edge conditions. Since there is no output schema, the description compensates by listing response fields. It also references related sibling tool for custom sizing.

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% (both event and topic have descriptions). The description goes far beyond by detailing each mode: event mode expects a Polymarket event slug and walks child markets for partition_check; topic mode uses a seed question to search related events and checks cross-event monotonicity. It provides examples and explains the internal logic, vastly enriching the 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: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It distinguishes from siblings like polymarket_edges and polymarket_fill_risk by explaining its unique algorithmic approach and providing specific usage modes (trending_scan, event, topic).

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 provides explicit when-to-use guidance: '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 and topic mode for cross-event scanning, and even mentions when to use 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

B3.1/5.0
Disambiguation2/5

The set is split between Wynncraft game data tools and a large Pipeworx data cluster, and within the Pipeworx cluster there is heavy overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (the beta is currently identical), ai_visibility_check and scan_competitor_ai_presence do essentially the same thing at different granularities, and six polymarket_* tools cover overlapping prediction-market functionality. An agent would frequently struggle to choose the right tool.

Naming Consistency3/5

Snake_case with a mostly verb_noun pattern dominates (ask_pipeworx, compare_entities, resolve_entity, validate_claim), and families like polymarket_* and pipeworx_* are internally consistent. However, there is a notable mix of noun-only tools (guild, item_database, leaderboard, player, news) and the server is named Wynncraft while the majority of tools are Pipeworx-branded, which breaks overall coherence.

Tool Count2/5

40 tools is well beyond the borderline range, and the count is inflated by redundancy: multiple ask_pipeworx variants, several overlapping polymarket tools, a memory trio, and subscription management that arguably belong to a separate server. The Wynncraft portion alone would be nicely scoped (~9 tools), but the merged surface feels heavy and unfocused.

Completeness4/5

The Wynncraft side offers solid read coverage of players, guilds, items, leaderboards, news, and online status, which is appropriate for the domain. The Pipeworx side covers lookup, grounded verification, comparison, research, prediction markets, subscriptions, memory, and feedback, leaving few obvious dead ends for the stated meta-purposes.

Resources