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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

A4.9/5.0
Behavior5/5

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

The description explains the internal logic: monotonicity checks, partition_sum checks, Jaccard similarity, placeholder filtering, and fill check against CLOB depth. It covers edge cases like skipped_low_similarity and partition filter. Annotations declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false, and the description reinforces these with concrete details. No 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 well-structured with clear sections (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK) and front-loaded with the core functionality. However, it is somewhat verbose, with many details that could be condensed. Still, every sentence adds value, and the structure aids readability.

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 thoroughly explains the response fields (opportunities[], partition_check, etc.) and the logic behind them. It covers the main use cases, edge cases, and practical trade considerations. The complexity of the tool is well-addressed, making it complete for an agent to understand and use correctly.

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 beyond the schema. It explains that 'event' accepts a slug or full URL, while 'topic' expects a seed question. It details the behavior for each parameter including the scanning logic and internal filters. The description provides practical usage advice that the schema alone does not.

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 finds arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes three modes (no args, event, topic) and explains each. The verb 'Find' with specific resource 'arbitrage opportunities' and the mention of techniques make the purpose specific. It differentiates 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 explicitly states when to use each mode: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. It provides guidance on what to pass and the type of input. It also mentions an alternative tool for custom sizing: 'For custom sizing use polymarket_fill_risk', helping the agent choose correctly.

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

A3.6/5.0
Disambiguation3/5

Many tools have distinct purposes, but there is overlap among query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and among prediction market tools. Detailed descriptions help differentiate, but the large number of tools increases chance of misselection.

Naming Consistency2/5

Naming is highly inconsistent, mixing snake_case and camelCase conventions. ClickUp tools use 'clickup_' prefix while Pipeworx tools have varied patterns (ask_, scan_, validate_, etc.). No unified convention across the set.

Tool Count2/5

35 tools is excessive for a server named 'Clickup', with only 6 ClickUp-specific tools. The remaining 29 are from Pipeworx, which is unrelated. The count is inappropriate for the server's stated purpose.

Completeness2/5

The ClickUp integration is incomplete, missing basic CRUD operations like update and delete tasks. The Pipeworx side is comprehensive but not relevant to the server's name. For a ClickUp server, coverage is poor.

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