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Arcgis Kansas

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

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint/idempotentHint annotations, the description discloses algorithmic details: Jaccard similarity threshold (≥0.30), placeholder filter (>20% returns null), fill-check behavior against live CLOB depth, and the meaning of realizable_edge_pp ≤ 0. This gives the agent full transparency about the tool's internal decision logic.

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 long (around 250 words) but uses structured section headers (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK) and front-loads the core purpose. Every sentence adds relevant detail for a complex tool, though it could be slightly tightened without losing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description explicitly documents the response shape (opportunities[] with fields, partition_check object) and edge cases (placeholder filters, low-similarity rejection, fill-check results). It covers the tool's modes and failure conditions, though it doesn't specify behavior when both arguments are passed or error handling, which is a minor gap.

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?

Although the input schema already describes each parameter, the tool description adds significant context: event is 'recommended for a specific market' with slug/URL examples, topic is for cross-event scanning with seed question examples, and the difference between them is explained in depth. This goes well beyond the schema's short 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 opens with a specific verb-object pair ('Find arbitrage opportunities on Polymarket') and names the detection methods (monotonicity violations + partition-sum checks). It then details three invocation modes (trending_scan, event, topic), which clearly distinguishes it from sibling tools like polymarket_edges and 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 Guidelines5/5

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

The description provides explicit when-to-use guidance: no args for trending scan, `event` for a specific market, `topic` for cross-event scanning. It also directs users to polymarket_fill_risk for custom sizing, naming an alternative tool, and explains the recommended mode for each scenario.

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

A3.5/5.0
Disambiguation1/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all route questions; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker all deal with prediction market edges). The inclusion of memory tools (remember, recall, forget) alongside research tools further blurs boundaries.

Naming Consistency2/5

Naming conventions are mixed: some tools use snake_case (ai_visibility_check), some use underscores with prefixes (ask_pipeworx, polymarket_arbitrage), and others are more generic (query_layer, layer_info). There is no consistent pattern across the set.

Tool Count2/5

With 34 tools, the set is overly large for a geospatial server; most tools are unrelated to ArcGIS Kansas (e.g., prediction market tools, general research tools). Only 3 tools (search_datasets, layer_info, query_layer) are pertinent, making the count excessive and unfocused.

Completeness1/5

The server claims to be an ArcGIS Kansas tool but provides only basic layer querying and dataset search. Missing essential GIS operations such as editing, spatial analysis, or advanced queries, making it severely incomplete for its stated purpose.

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