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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

A5/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint true, and destructiveHint false. The description adds substantial behavioral context: semantic anchor for cross-event pairs (Jaccard similarity ≥0.30), partition filter for placeholder slugs, fill check against live CLOB depth. 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.

Conciseness5/5

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

Although lengthy, every sentence adds value. The description is structured logically: main purpose, then detailed breakdown of each mode with examples, then behavioral details like semantic anchor and fill check. Front-loaded with core function. No wasted words.

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 tool's complexity (two optional parameters, no output schema), the description covers all needed aspects: input modes, internal processing (monotonicity, partition checks, fill check), output structure (opportunities[], partition_check), and edge cases (placeholder filtering, fill check thresholds). It is sufficiently complete for effective use.

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% (both event and topic described). The description adds significant meaning beyond the schema: event can accept full URLs, topic triggers a cross-event scan with internal search logic. It provides examples of valid slugs and topic questions, greatly aiding parameter understanding.

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 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 Guidelines5/5

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

Explicit guidance is provided for each mode: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. The description also explains when not to trade based on fill check results, offering clear usage boundaries.

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

Several tools occupy heavily overlapping space: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same router, with the beta version explicitly noted as currently identical to the stable one. The six polymarket_* tools plus bet_research and macro_snapshot/indicator further blur boundaries, so an agent could easily route a query to the wrong entry point despite the detailed descriptions.

Naming Consistency4/5

Names are consistently snake_case and mostly follow a verb_first or domain_prefix pattern (ask_pipeworx, resolve_entity, validate_claim, polymarket_edges). Minor deviations like entity_profile, indicator, macro_snapshot, and recent_alerts use noun phrases, but the style is still predictable and readable.

Tool Count2/5

At 33 tools, the surface is heavy and exceeds the 25+ threshold for 'too many'. While the server covers many domains, several tools are near-duplicates or conveniences (ask_pipeworx_beta, scan_competitor_ai_presence, indicator) that could be consolidated.

Completeness5/5

For its apparent scope—structured data Q&A, grounded research, entity comparison, prediction-market analysis, subscriptions, and memory—the tool set covers the full lifecycle: query, ground, verify, research, compare, monitor, subscribe, alert, and manage state. There are no obvious dead ends; even supporting workflows like discover_tools and suggest_questions are provided.

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