Skip to main content
Glama

Openrouter

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

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. The description adds rich behavioral context: threshold details (3pp, 0.30 Jaccard), placeholder filtering, fill check logic, and fallback behavior. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is very long and detailed, which provides completeness but sacrifices conciseness. It is well-organized with logical sections, but could be trimmed for quicker scanning by an AI agent.

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 lacking an output schema, the description thoroughly details the response structure (opportunities[], partition_check object, fill check results) and covers edge cases, semantic anchors, and filtering rules. It is fully self-contained for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% description coverage for both parameters, but the tool description adds substantial meaning beyond the schema: examples of valid values ('fed-decision-may-2026'), the purpose of each parameter, and how they affect scanning behavior. This enriches understanding but is somewhat verbose.

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 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks' and distinguishes three modes (trending_scan, event, topic), making the purpose and scope unambiguous.

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 given for each mode: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. It also advises when not to execute a trade based on the fill check results and references polymarket_fill_risk for custom sizing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Openrouter toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation3/5

Several tools overlap in purpose: ask_pipeworx and ask_pipeworx_beta are explicitly identical today, and the polymarket_edges, polymarket_arbitrage, bet_research, and polymarket_fill_risk tools all orbit market-opportunity analysis from slightly different angles. The descriptions are unusually detailed and often say when to prefer one tool over another, but an agent must read carefully to avoid misselection.

Naming Consistency4/5

Names are consistently snake_case and mostly follow a verb_noun pattern (list_models, get_model, resolve_entity, validate_claim, scan_dependency), with predictable domain prefixes like polymarket_* and pipeworx_*. A few noun-first names like entity_profile, bet_research, and ai_visibility_check deviate slightly, but the overall convention is readable and coherent.

Tool Count2/5

34 tools is well into the 'too many' range, especially for a server named Openrouter that actually spans several unrelated domains: model catalog, Pipeworx data retrieval, Polymarket analysis, memory, subscriptions, and website tooling. Many individual tools are justified, but the set is overstuffed and would be better split into focused servers.

Completeness3/5

Each sub-domain is reasonably covered: model catalog has list/get/compare, memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and Pipeworx querying has multiple modes plus discovery. However, a server named Openrouter exposes no way to actually run completions or route requests through OpenRouter, and the unrelated bundled domains make the overall surface feel scattered rather than complete.

Resources