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Usgs Earthquakes

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?

Beyond the annotations (read-only, open world), the description discloses rich behavioral detail: walks child markets, checks date-axis/threshold-axis ordering, computes partition sums, applies semantic anchor Jaccard similarity, filters placeholder slugs, and performs a fill check against live CLOB depth with the warning 'realizable_edge_pp ≤ 0 ... do not trade it.' 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.

Conciseness4/5

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

The description is long but well-structured with bolded section labels (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK) and a front-loaded purpose statement. Every sentence carries useful information, though it could be tightened for a perfect score.

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?

This is a complex tool with no output schema, but the description fully covers the response shape (opportunities[], partition_check), edge cases (placeholder filters, low similarity), and trade advisories. It also mentions the alternative sizing tool, making it complete for an agent to decide and invoke correctly.

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 schema already covers both parameters, the description adds substantial semantics: concrete examples like 'fed-decision-may-2026', explains the exact behavior in each mode, and notes that full Polymarket URLs are accepted. This goes well beyond the schema's brief 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 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks' — a specific verb, resource, and method. It distinguishes this from sibling tools like polymarket_edges by focusing on arbitrage rather than just edges or tracking.

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 describes three usage modes: no-args trending_scan, event mode, and topic mode, with clear recommendations ('event (recommended for a specific market)'). It also points to an alternative for sizing: 'For custom sizing use polymarket_fill_risk,' and explains the relative advantages of cross-event scanning.

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
Disambiguation1/5

The tool set is dominated by tools unrelated to USGS earthquakes (e.g., Polymarket betting, company profiles, memory operations). An agent would find it nearly impossible to distinguish the few earthquake-specific tools from the multitude of unrelated ones, leading to severe misselection.

Naming Consistency3/5

Most tool names follow a verb_noun pattern with underscores (e.g., search_earthquakes, count_earthquakes), which is consistent. However, the variety of verbs and domains creates a sense of incoherence, and some tool names are overly generic (e.g., process, run) in the broader context, though those are not present here. The naming pattern is acceptable but the inconsistency in domain scope reduces clarity.

Tool Count1/5

With 29 tools but only 3 directly related to earthquakes, the tool count is grossly inappropriate. The server's name suggests a focused purpose, but the vast majority of tools belong to other domains (e.g., Pipeworx queries, Polymarket betting, company data). This extreme mismatch makes the tool set bloated and misleading.

Completeness2/5

For earthquake data, the server provides only search, count, and get by ID. Missing are common operations like listing recent quakes, subscribing to alerts, or updating/correcting data. The coverage is minimal and insufficient for a comprehensive earthquake tool server, leaving significant gaps that agents could not work around.

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