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Edmtrain

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

A5/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, non-destructive. Description adds detailed behavioral traits: scanning top markets, semantic similarity filtering (0.30 Jaccard), placeholder filtering, partition sum checks, fill check against live CLOB depth. Fully consistent 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.

Conciseness5/5

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

Despite length, the description is well-structured with clear sections (modes, semantic anchor, partition filter, response, fill check, related tool). Every sentence adds essential information without redundancy. Front-loaded with purpose.

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?

No output schema, so description fully describes response fields (opportunities[], partition_check with subfields). Covers edge cases (skipped_low_similarity, placeholders, fill check conditions). Provides complete guidance for correct tool usage.

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 coverage is 100% with decent descriptions. The tool description significantly enhances parameter understanding by providing concrete examples (slugs, seed questions) and explaining behavior differences (single-event vs cross-event). Also notes that full URLs are accepted for event.

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 finds arbitrage opportunities via specific methods (monotonicity violations + partition-sum checks) and distinguishes two modes (event/topic). It implicitly differentiates from siblings by referencing polymarket_fill_risk for custom sizing.

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 tells when to call with no args (trending scan), pass event, or pass topic. Recommends event for specific markets and explains cross-event mode catches patterns missed by single-event. Also advises to avoid trading when realizable_edge_pp ≤ 0, guiding decision-making.

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

Several tools have overlapping or near-identical purposes: ask_pipeworx and ask_pipeworx_beta are currently functionally identical, ask_pipeworx_grounded is the same router with an extraction step, and discover_tools vs suggest_questions both serve as 'what can I do here' entry points. The polymarket_* family is more distinct, but the ask_pipeworx/deep_research overlap alone makes tool selection genuinely ambiguous.

Naming Consistency4/5

The vast majority of tools follow lowercase snake_case with recognizable domain prefixes (ask_pipeworx*, polymarket_*, pipeworx_*), which is a decent pattern. However, there are bare-noun tools (events, locations, recall, forget) and mixed verb-first vs noun-first ordering (list_subscriptions vs entity_profile, scan_dependency vs polymarket_edges), so it is not perfectly uniform.

Tool Count2/5

33 tools is well above the comfortable range and feels heavy even for a broad data-research platform. Many tools are narrow variations (five polymarket analysis tools, four ask_pipeworx variants, three memory tools) that could plausibly be consolidated or exposed as parameterized modes rather than separate top-level tools.

Completeness4/5

For the actual domain suggested by the tool names and descriptions—structured data research, entity profiling, claim verification, and prediction-market analysis—the surface is quite complete: lookup, grounded answers, deep research, comparisons, recent-change tracking, subscriptions, memory, and arbitrage/fill-risk analysis are all covered. However, relative to the server name 'Edmtrain', the event-discovery surface is extremely thin (only events and locations), which is a notable mismatch.

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