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Abn Lookup

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

A4.9/5.0
Behavior5/5

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

Annotations mark the tool read-only and non-destructive, and the description adds substantial behavioral detail: partition filtering, similarity thresholds, fill-check against live CLOB depth, and the difference between theoretical and realizable edge. No contradiction with annotations exists.

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

Conciseness5/5

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

Dense but every sentence carries operational value: mode selection, examples, filters, response fields, and fill-check caveat. It is front-loaded with the core purpose and uses clear mode headings to keep a complex tool navigable.

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 description fully covers invocation patterns, parameter semantics, response shape, edge-case filters, and real-world trading caveats. Since there is no output schema, the explicit response field list and fill-check explanation are especially valuable and sufficient.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaningful semantics beyond the schema: event mode checks date/threshold ordering plus partition sum, while topic mode flattens related events and catches cross-event patterns. It also documents the no-arg behavior, which the schema cannot express.

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?

States a clear specific action: find arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It also distinguishes operational modes (trending_scan, event, topic) and references polymarket_fill_risk for custom sizing, helping the agent tell it apart 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 Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance: no args for trending scan, event for a specific market, topic for cross-event scanning, and names polymarket_fill_risk for custom sizing. It also tells the agent when not to trade (realizable_edge_pp <= 0), making decisions concrete.

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

A3.8/5.0
Disambiguation2/5

Several tools have unclear or overlapping boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, while ask_pipeworx, deep_research, and validate_claim all handle factual lookup/research tasks. The five polymarket_* tools plus bet_research also overlap enough that an agent could easily pick the wrong entry point despite verbose descriptions.

Naming Consistency3/5

All names are snake_case and generally descriptive, but conventions are mixed: some are verb-first (ask_pipeworx, resolve_entity, validate_claim), some are noun-first (abn_lookup, entity_profile, polymarket_edges), and prefixes like pipeworx_ and polymarket_ are used inconsistently. It is readable but not a clean, predictable pattern.

Tool Count2/5

34 tools is far too many for a server named 'Abn Lookup' — most of the surface is a broad data-research platform with prediction-market analysis, memory, subscriptions, feedback, and web utilities. The count could fit a large platform, but under this server name and with several near-duplicate entry points, it feels bloated.

Completeness4/5

For a read-only lookup/research server, coverage is strong: ABR lookups, entity resolution, single-query research, grounded verification, deep research, company profiles, comparisons, change feeds, prediction-market analysis, memory, and subscriptions are all represented. Minor gaps exist (e.g., no ACN search-by-name, no order execution), but no core workflow dead-ends.

Resources