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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.

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses key behavioral traits beyond annotations: Jaccard similarity filter (SEMANTIC ANCHOR), placeholder slug filtering (PARTITION FILTER), and fill check with realizable edge calculation. Annotations already mark it as read-only and idempotent, which the description aligns with, and no contradictions are present.

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 dense but well-structured with sections (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK). It front-loads the core purpose. While slightly long, the complexity of the tool justifies the length. A minor reduction in detail on edge cases could improve conciseness.

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?

Despite no output schema, the description explains the response structure (opportunities array with fields, partition_check object) and covers edge cases like skipped_low_similarity and placeholders_filtered. It also references polymarket_fill_risk for custom sizing, showing thoroughness. The tool's behavior is fully documented.

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%, but the description adds significant context: it explains that no args triggers trending scan, event and topic modes have specific meanings, and provides examples. The description also details the partition check and fill check behavior tied to the parameters, adding 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: finding arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes between three modes (no args, event, topic) with specific examples, making it easy to understand what the tool does relative to siblings.

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 explicitly instructs when to use each mode: no args for trending scan, event for specific market, topic for cross-event scan. It provides example inputs and explains the partition check and fill check. However, it does not directly compare with sibling tools like polymarket_edges or polymarket_edge_tracker, which could be alternatives.

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
Disambiguation3/5

Most tools have strong, detailed descriptions with explicit usage guidance, but a few clusters are genuinely ambiguous: ask_pipeworx_beta is currently an exact duplicate of ask_pipeworx, and the Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker) overlap heavily in purpose. The descriptions help differentiate them, but an agent could still easily select the wrong variant.

Naming Consistency4/5

All tool names are snake_case and most follow an imperative verb-first pattern such as resolve_entity, subscribe, or validate_claim. A few noun-style names like entity_profile, bet_research, and interaction_count deviate, but the consistent underscore style and clear prefixes like polymarket_ and pipeworx_ keep the set predictable.

Tool Count2/5

At 33 top-level tools, the surface is heavy, and several tools are near-duplicates or narrow variants of the same core capability. The broad scope explains some of the count, but the agent-facing API would be cleaner with fewer, more consolidated entry points.

Completeness5/5

The set provides strong lifecycle coverage for its main workflows: querying and grounding, deep research, entity resolution, company profiling, comparisons, Polymarket edge analysis with fill-risk checks, memory storage, and subscription management. There are no obvious dead ends that would prevent an agent from completing a typical task.