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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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint as true and destructiveHint false. The description adds extensive behavioral detail: how it scans markets, computes partition checks, performs fill check against live CLOB depth, and reasons about realizable 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 front-loaded with the core purpose and structured into clear sections (modes, semantic anchor, partition filter, response, fill check). Some sentences are dense but necessary; a little verbose in places but overall efficient for the tool's complexity.

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 intricacy (two parameters, no output schema), the description thoroughly explains inputs, modes, internal logic (Jaccard similarity, placeholder filter), response structure, and even references a sibling tool for custom sizing. An agent can understand exactly how to invoke and interpret results.

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% and both parameters have descriptions, but the tool description adds substantial meaning: explains what event slugs/URLs are accepted, what topic queries work, and gives examples. It also clarifies the differing behavior between event and topic modes, going far beyond schema basic type info.

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 between three modes (no args, event, topic) and explains each, making the purpose specific and distinct from sibling tools.

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?

Provides explicit guidance on when to use each mode: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. Includes recommendations and conditions (e.g., partitions with >20% placeholder fraction return null). Lacks explicit 'when not to use', but context is clear.

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

A3.9/5.0
Disambiguation3/5

Most tools have distinct, well-scoped purposes, but several question-answering/research tools sit close together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim can all be selected for factual questions. The descriptions are detailed enough to reduce ambiguity, but ask_pipeworx_beta is currently identical to ask_pipeworx, and discovery helpers like discover_tools, suggest_questions, and pipeworx_trending also overlap somewhat.

Naming Consistency4/5

Names are uniformly snake_case and mostly follow a verb_noun pattern such as build_url, list_subscriptions, resolve_entity, and validate_claim. The polymarket_* and pipeworx_* prefixes form a readable convention, though a few names like pipeworx_feedback and polymarket_arbitrage are noun-phrases rather than verb-first actions.

Tool Count2/5

34 tools is well past the 25+ threshold where even a broad platform starts to feel bloated. The set mixes data research, prediction-market tooling, URL utilities, memory, subscriptions, feedback, and npm scanning, which would be more coherently split across focused servers.

Completeness3/5

The core research workflows are thoroughly covered: routing, grounded answers, deep research, entity resolution, comparisons, claim validation, discovery, alerts, and memory all exist. However, the URL utility and dependency-scanning side domains feel tacked on and incomplete, and there is no dedicated tool to fetch an arbitrary pipeworx:// citation record even though such URIs are returned throughout.

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