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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.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark it as read-only, idempotent, and non-destructive. The description adds extensive behavioral context: semantic anchor (Jaccard similarity), partition filter (placeholder slugs dropped), fill check against live CLOB depth, and realizable vs theoretical edge. 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 with clear sections (modes, semantic anchor, partition filter, fill check) and uses punctuation effectively. It is somewhat lengthy but every sentence adds value. Could be slightly more concise.

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, so the description must explain return values. It does so clearly: opportunities[] with fields, and in event mode partition_check object. It also covers edge cases like fill check and custom sizing. Comprehensive for the tool's complexity.

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 having descriptions. However, the tool description adds significant meaning: acceptable formats for event slug, full URLs accepted, explanation of topic mode as seed question. This goes well 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 defines the tool's purpose: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It distinguishes three modes (trending_scan, event, topic) and explains what each does. This clearly separates it from sibling tools like polymarket_edges or polymarket_edge_tracker.

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: no args for trending scan, 'event' for specific event, 'topic' for cross-event scanning. It explains the recommended use case for event mode. However, it does not explicitly compare to sibling tools or state when not to use this tool, though the context is implied.

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

Several tools overlap heavily: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and ask_pipeworx_grounded shares the same router. The universal ask_pipeworx router also subsumes many domain-specific tools (attom_*, entity_profile, etc.), making it unclear when to use the specialist tools versus the catch-all.

Naming Consistency3/5

All names are snake_case and mostly descriptive, but conventions vary: ask_* and attom_* prefixes coexist with bare verbs (remember, forget, subscribe), noun phrases (entity_profile, polymarket_edges), and adjective-prefixed names (recent_alerts, recent_changes). The pattern is readable but not uniform.

Tool Count2/5

39 tools is well over the 25+ threshold for a heavy surface, especially for a server named 'Attom' that also includes memory, subscriptions, feedback, npm scanning, and AI-visibility tools beyond real estate. Many tools could be consolidated (e.g., the three ask_pipeworx variants, the six polymarket tools).

Completeness4/5

The real estate domain is well covered (search, detail, AVM, rental AVM, sales history, trends, assessment, schools), and the broader data platform includes discovery, grounded answers, entity profiles, comparisons, claim validation, subscriptions, and memory. Minor gaps exist only around edge features like OAuth-gated subscription persistence.

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