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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?

Annotations indicate read-only, open-world, idempotent, non-destructive. The description adds extensive behavioral details: monotonicity checks, partition-sum logic, semantic anchor, partition filter, fill check, response structure. No contradiction 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 detailed and front-loaded with the main purpose. While lengthy, every sentence adds value given the tool's complexity. A slightly more concise version could be possible, but current structure is well-organized.

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 two optional parameters with distinct modes and no output schema. The description fully covers parameters, behavior, output format, and caveats (fill check, semantic anchor, partition filter). Annotations provide safety context. No gaps remain.

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 description coverage is 100%, but the description adds significant value beyond the schema: explains event slugs vs topics, provides usage examples, details internal processing logic, and describes the fill_check feature. This greatly exceeds the baseline of 3.

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 it finds arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes three modes (no args, event, topic) with specific verb+resource, differentiating 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?

Explicitly states when to use each parameter: no args for trending scan, event for single-market, topic for cross-event scanning. Provides examples, recommendations (e.g., 'recommended for a specific market'), and warns against trading when fill check fails.

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

Several tools form overlapping clusters (ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded, the five polymarket_* tools, and discover_tools vs suggest_questions) that could cause misselection on first glance. The detailed descriptions mostly clarify the boundaries, but the overlaps are real and require careful reading.

Naming Consistency4/5

The naming is overwhelmingly snake_case with a verb_noun pattern (ask_, extract_, generate_, list_, resolve_, subscribe), which is predictable. A few noun-style or special-form names (entity_profile, html_to_text, recent_changes, polymarket_edges) break the pattern, but these are minor deviations.

Tool Count2/5

At 34 tools the surface is heavy, especially for a server named 'Htmltext' where only 4 of 34 tools relate to HTML. Even accounting for the broad data/research domain, the set includes several redundant research and Polymarket helpers that push it past a well-scoped count.

Completeness4/5

The major subdomains are well covered: HTML extraction, entity/data research, prediction-market analysis, memory, and subscriptions all have the core operations needed with no obvious dead ends. Some niches are shallow (HTML lacks a general fetch/render tool; scan_dependency is a one-off), but agents can work around these gaps.

Resources