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Europeana

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?

The description discloses extensive behavioral details beyond the annotations: the scanning process, monotonicity checks, partition-sum checks, fill check against CLOB depth, semantic anchor constraints (Jaccard similarity), and partition filter (placeholder slugs). Annotations already indicate read-only and idempotent behavior, and the description reinforces this without contradiction.

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 details, but could be slightly more concise without losing key information. Every sentence adds value, but the length may slow down parsing.

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 the lack of an output schema, the description provides a comprehensive overview of the response structure (opportunities[], partition_check fields, fill check details). It also explains edge cases (semantic anchor, partition filter, thin legs) and directs users to a related tool for custom sizing. No critical information is missing.

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?

While the input schema already covers both parameters (event, topic) with descriptions, the tool's description adds substantial meaning: it explains the modes, provides example slugs ('fed-decision-may-2026'), clarifies that full URLs are accepted, and describes the cross-event scanning logic. This goes well beyond the schema's basic 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?

The description clearly states the tool's purpose: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It also outlines three distinct modes (no args, event, topic) and their specific use cases, effectively distinguishing itself from sibling tools like polymarket_edges and polymarket_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 Guidelines5/5

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... pass event for... or topic for...' It recommends event mode for specific markets, explains that cross-event mode catches patterns missed by single-event mode, and directs users to polymarket_fill_risk for custom sizing. This clearly differentiates usage scenarios.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., three versions of ask_pipeworx for similar tasks, and several research/analysis tools (bet_research, deep_research, entity_profile) with unclear boundaries. The mix of Europeana-specific tools with a broad research toolkit creates confusion.

Naming Consistency2/5

Tool names are inconsistent, mixing snake_case (ai_visibility_check, ask_pipeworx), verb_noun patterns (compare_entities, resolve_entity), and short names (search, record, forget). No clear naming convention is followed throughout the set.

Tool Count2/5

33 tools is excessive for a Europeana-focused server, as only 3 tools (search, record, search_within) are directly related to Europeana. The rest are a broad, unrelated toolkit, making the server feel like a kitchen sink rather than a cohesive collection.

Completeness2/5

The Europeana-specific tool surface is severely incomplete, lacking browse collections, advanced filters, or entity linking. The inclusion of many unrelated tools does not compensate for the gaps in the core domain, resulting in a poorly scoped offering.

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