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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

A4.9/5.0
Behavior5/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false) align with the description. The description adds extensive behavioral details: scanning logic, Jaccard similarity anchor, partition filter, fill check against live CLOB depth, and reporting of skipped_low_similarity count. No contradictions.

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 dense but front-loaded with core functionality. Every sentence adds value, though it could be slightly more structured with bullet points. No unnecessary words; it is efficient for the information conveyed.

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 (multiple modes, arbitrage detection, fill check, semantic anchor, partition filter), the description covers all aspects. It explains input choices, internal logic, output structure, and references sibling tools for further details. No output schema exists, but the description compensates well.

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 has 100% coverage with descriptions for both parameters. The description adds significant meaning: explains mode switching, provides example slugs and seed questions, and details what happens internally (walks child markets, checks ordering, computes partition_check, etc.), greatly enhancing beyond schema.

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 title 'Polymarket Arbitrage' and description clearly state it finds arbitrage opportunities via monotonicity violations and partition-sum checks. It distinguishes three modes (trending scan, event-specific, cross-event) and contrasts with sibling tools like polymarket_edges and polymarket_fill_risk, providing a specific verb and resource.

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 describes when to use each parameter: no args for trending scan, 'event' for a specific market (recommended with slug examples), and 'topic' for cross-event scanning. Also mentions when not to trade (if realizable_edge_pp ≤ 0) 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.

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TDQS

A3.7/5.0
Disambiguation2/5

Several tool clusters are hard to tell apart: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical routers (beta currently behaves exactly like stable), and the six polymarket_* tools plus bet_research all overlap around edge and arbitrage discovery. The descriptions are detailed and help, but an agent must read carefully to avoid misselecting a sibling tool.

Naming Consistency3/5

Names are consistently lowercase snake_case, but the verb/noun ordering is mixed: verb-first names (ask_pipeworx, list_categories, resolve_entity) coexist with noun-first names (polymarket_edges, entity_profile, pipeworx_feedback, recent_alerts) and bare verbs (remember, recall, forget). Readable overall, but the pattern is not systematic.

Tool Count2/5

34 tools is well beyond the 25+ threshold and spans at least six loosely related domains (news, structured data research, prediction markets, AI visibility, memory, subscriptions), making the server feel like a multi-product grab bag. Meta-tools like discover_tools, suggest_questions, and pipeworx_trending add further navigation overhead.

Completeness4/5

Within each bundled domain the lifecycle is well covered: data lookup has routing, grounded mode, deep research, entity resolution, comparison, and claim validation; Polymarket has research, arbitrage, edge, fill-risk, and cross-venue spread tools; memory and subscriptions each have full CRUD-ish flows. Minor gaps like subscription updating or direct article-by-ID fetching are workarounds rather than dead ends.