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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

A4.6/5.0
Behavior5/5

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

Annotations (readOnlyHint: true, idempotentHint: true, destructiveHint: false) clearly indicate no side effects. The description goes far beyond annotations by detailing internal logic: semantic anchor with Jaccard similarity threshold, partition filter that drops placeholder slugs, and fill check that checks live CLOB depth. It warns when signals should not be traded (realizable_edge_pp <= 0). This is highly transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long and dense with technical jargon (monotonicity violations, partition-sum checks, Jaccard similarity). While it is well-structured with sections (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK), it could be more concise. Approximately 280 words; trimming could improve readability without losing essential detail.

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 has no output schema, but the description comprehensively explains the response structure (opportunities[], partition_check object with fields). It covers edge cases (skipped_low_similarity, placeholders_filtered) and gives detailed behavior for event and topic modes. Given the tool's complexity and zero output schema, the description is as complete as needed.

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% with both parameters documented. The description adds significant meaning: event accepts slug or URL, topic accepts seed questions. It explains behavior for each parameter (e.g., topic mode searches related events, flattens markets, runs comparator). This adds value beyond 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 specifies two distinct modes (event and topic) with clear verb+resource relationships, and it distinguishes itself from sibling tools like polymarket_edges and polymarket_fill_risk by focusing on arbitrage detection rather than edge tracking or fill risk.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use each mode: 'Call with NO args for a trending_scan,' 'event (recommended for a specific market),' and 'topic (for cross-event scanning).' It explains the strengths of cross-event mode over single-event mode. However, it lacks explicit 'when not to use' statements, such as pointing to polymarket_fill_risk for custom sizing (though it mentions that tool at the end).

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

A4.1/5.0
Disambiguation2/5

Multiple tools blur together: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-variants, and the six polymarket_* tools plus bet_research heavily overlap in purpose. Descriptions are detailed and cross-reference each other, but an agent must read very long definitions to avoid misselection.

Naming Consistency4/5

The set is consistently snake_case with helpful domain prefixes like ask_pipeworx, polymarket_*, and scan_*. Deviations such as deep_research, entity_profile, recent_alerts, and the bare verbs remember/recall/forget break a strict verb_noun pattern but remain predictable.

Tool Count3/5

34 tools is heavy for one server, and several groups could plausibly be consolidated. However, the platform spans data lookup, research, prediction markets, memory, subscriptions, and utilities, so the breadth partially justifies the count.

Completeness5/5

The surface covers lookup, grounded verification, deep research, entity comparison, claim validation, prediction-market analysis, memory CRUD, subscription lifecycle, and discovery. There are no obvious dead ends, and gaps are minor or workaroundable.

Resources