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Destatis

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

A4.5/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive, open-world. The description adds significant behavioral details: the arbitrage computation logic, fill check using live CLOB depth, semantic anchor (Jaccard similarity), partition filter (placeholder fraction), response fields, and the condition for null arb signal. 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.

Conciseness3/5

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

The description is very detailed but somewhat verbose. It is well-structured with front-loaded purpose and uses bold mode names. However, some sections (e.g., the fill check explanation) could be more concise without losing clarity. It earns its length but could be trimmed.

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 (three modes, multiple checks, fill analysis) and no output schema, the description covers all necessary information: how to call with no args, event, or topic; response structure (opportunities array, partition_check fields); fill check and when to avoid trading; prerequisites (slugs, URLs); and a reference to polymarket_fill_risk for custom sizing.

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% with both parameters described in the input schema. The description adds extra context: for event, it gives examples of slugs and states that full URLs are accepted; for topic, it provides examples and explains the cross-event search behavior. This goes beyond the schema's basic descriptions.

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 the tool's core purpose: finding arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It names specific resources (Polymarket markets) and actions (scan, check, etc.) and distinguishes three modes (no args, event, topic) with clear functionality. This differentiates it from siblings like polymarket_edges or 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 Guidelines4/5

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

The description provides explicit guidance on when to use each mode: no args for trending scan, event for specific market, topic for cross-event scanning. It explains the benefit of cross-event mode and includes a fill check warning ('do not trade it' when realizable_edge_pp <= 0). However, it does not explicitly contrast with sibling tools for similar tasks.

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
Disambiguation2/5

The ask_pipeworx family—ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded—plus deep_research all describe the same router under slightly different modes, and the six polymarket tools overlap heavily around edge detection and arbitrage. ai_visibility_check and scan_competitor_ai_presence are also near-duplicates, so agents will frequently have to choose between tools that appear to do the same thing.

Naming Consistency3/5

All names use snake_case and several families share prefixes (ask_pipeworx, polymarket_, pipeworx_, destatis_), which helps discoverability. However the pattern is not consistent: bare verbs (remember, recall, forget), adjective_noun phrases (recent_alerts, recent_changes), and noun_noun names (entity_profile, bet_research) are all mixed.

Tool Count2/5

With 33 tools, the surface is well past the 25+ threshold and mixes unrelated concerns: Destatis statistics, a general data router, prediction-market analytics, memory, and AI-marketing scans. The count could be justified if split into separate servers, but as one set it feels over-stuffed.

Completeness4/5

For the broad data-retrieval/research purpose the descriptions reveal, coverage is strong: lookup, grounded answers, validation, entity resolution, comparison, change feeds, subscriptions, memory, and Destatis search/table are all present. The only notable weakness is that the Destatis-specific surface is just search-and-fetch, which is thin for a server literally named Destatis, but this is offset by the general router.

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