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Glama

Latam Validate

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 already declare readOnlyHint=true, and the description reinforces that the tool is analytical (no mutations). It adds extensive behavioral context: the logic of partition_sum checks, similarity anchors, placeholder filters, and the fill check against live CLOB depth. It also explains when results should not be traded (realizable_edge_pp ≤ 0). No contradictions 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.

Conciseness4/5

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

The description is detailed and well-structured, starting with the main purpose followed by mode-specific guidance, then response format. However, it is fairly long (several paragraphs) and includes technical jargon (Jaccard similarity, CLOB depth, placeholder fraction) that could be streamlined for quicker understanding. Still, every sentence adds value.

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 (arbitrage detection with multiple modes, similarity checks, response structure with gaps, partition checks, fill checks), the description is remarkably complete. It explains the output fields, edge cases (skipped_low_similarity, placeholders), and when to consider the results actionable. No output schema exists, so the description appropriately covers return values.

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?

Input schema covers 100% of parameters, but the description adds significant value: it explains that omitting both args triggers a trending scan, provides examples of valid event slugs and topic seeds, and details the internal logic for each mode (e.g., partition_check, Jaccard similarity). This goes well beyond the schema 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 finds arbitrage opportunities via monotonicity violations and partition-sum checks, with three distinct modes (trending scan, event-specific, cross-event topic). It is specific about the verb 'find' and the resource 'arbitrage opportunities on Polymarket'. The detailed behavior distinguishes it from sibling tools 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 Guidelines5/5

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

The description explicitly explains when to use each mode: no args for trending scan, event for a specific market (recommended), topic for cross-event scanning. It provides guidance on what arguments to pass (event slug, topic seed) and when not to trade (realizable_edge_pp ≤ 0). It also mentions an alternative tool (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

A3.6/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route the same 5,702 tools with only subtle differences, and ai_visibility_check is essentially a single-entity subset of scan_competitor_ai_presence. The memory trio (remember/recall/forget) and subscription tools also sit awkwardly alongside the data-query tools, making selection genuinely ambiguous.

Naming Consistency2/5

Naming mixes verb_noun (validate_cnpj, resolve_entity, compare_entities), noun_verb (bet_research, entity_profile, recent_changes), and bare nouns with inconsistent suffixes (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk). The ask_pipeworx family uses inconsistent qualifiers (beta vs grounded), and validate_* is used for both checksum-only tools and full lookups.

Tool Count2/5

36 tools is excessive for a server ostensibly named 'Latam Validate' — only 5 tools relate to LATAM validation while the rest form a sprawling general-purpose data and prediction-market platform. Many tools could be consolidated (the ask_pipeworx family, the polymarket_* family, the memory trio), suggesting the set is over-scoped for any single agent's typical workflow.

Completeness2/5

For the stated LATAM validation purpose, coverage is thin: only Brazil (CPF/CNPJ/CEP/banks) and Mexico (CLABE) are covered, with no validators for other LATAM jurisdictions. For the broader Pipeworx data platform, the surface is extensive but has notable gaps — grounded retrieval, claim verification, and arbitrage tools exist, yet many LatAm-specific data sources and common validation formats (RFC, RUT, DNI, CURP) are absent.

Resources