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Glama

Futuur

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

A4.9/5.0
Behavior5/5

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

Annotations already declare the tool read-only, open-world, idempotent, and non-destructive. The description adds substantial operational context: it walks child markets, checks date/threshold ordering, applies Jaccard similarity threshold (≥0.30), drops placeholder slugs, and explains the fill check against live CLOB depth with a precise behavioral rule ('do not trade it'). This exceeds what annotations could convey.

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 densely informative, with clear structure: first sentence states purpose, then each mode is explained in turn, and return fields are enumerated. No filler sentences, though it could be slightly tightened by moving the fill-check explanation to a separate section. Still, every sentence earns its place given the tool's 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?

With no output schema, the description fully specifies the response structure (opportunities[], partition_check, fill check fields). It also covers edge cases (skipped_low_similarity, placeholder filter, null arb signal) and the no-argument defaults. Combined with the rich annotations, this is a complete, self-contained specification for a complex 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 for both parameters is 100%, but the description goes far beyond the schema. It explains real-world usage examples ('fed-decision-may-2026'), accepts full URLs, clarifies that topic mode 'searches related events across the platform', and describes the internal processing for each parameter. This adds significant semantic meaning beyond the schema's bare definitions.

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 opens with a specific verb and resource: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It clearly distinguishes from sibling tools like polymarket_edges and polymarket_edge_tracker by naming the exact detection methods and the multiple scan 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?

Provides explicit when-to-use guidance: no args for trending_scan of top ~200 markets, 'event' for single-market analysis, 'topic' for cross-event scanning. It also names an alternative tool for custom sizing ('For custom sizing use polymarket_fill_risk') and gives a clear do-not-trade rule when realizable edge is ≤0.

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

A3.7/5.0
Disambiguation2/5

Multiple tools have overlapping or near-identical purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions with varying degrees of grounding. The polymarket_* family (edges, arbitrage, fill_risk, edge_tracker) and bet_research also create boundary confusion. An agent would struggle to consistently select the correct tool without deep reading of each description.

Naming Consistency3/5

Most tools follow a verb_noun snake_case pattern (search_markets, get_market, compare_entities, resolve_entity), but there are clear outliers like pipeworx_trending, recent_alerts, top_markets, and pipeworx_feedback which use adjective_noun or noun_adjective forms. The pattern is mostly consistent but has enough deviations to feel mixed.

Tool Count2/5

With 34 tools, the surface is decidedly heavy. Many tools serve entirely different domains (memory, subscriptions, AI visibility, npm dependency scanning, cross-venue arbitrage) rather than a unified purpose. This feels like several server concepts merged into one, making the count inappropriate for a single coherent server.

Completeness3/5

The data-research side is fairly comprehensive: querying, grounding, comparisons, profiles, claim validation, entity resolution, change tracking, and memory are all covered. However, for the nominal Futuur prediction-market domain, only read-only market lookup exists — no trading, account management, or order placement. Subscription CRUD is also missing an update operation, and several research tools only cover US public companies and specific data sources.

Resources