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Opentopography

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.

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses extensive behavioral traits beyond the annotations: it walks child markets, checks ordering, computes partition checks, uses Jaccard similarity for cross-event pairs, filters placeholders, and performs a fill check against live CLOB depth. Annotations already indicate readOnly, idempotent, non-destructive, but the description adds rich context. 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, with clear sections for each mode and fallback behavior. While it is somewhat verbose, every sentence adds value and contributes to understanding. It could be slightly shortened, but the structure is effective for an AI agent.

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?

Given the complexity of the tool and the absence of an output schema, the description covers the input modes, behavior, response structure (opportunities[], partition_check, fill check), and trade recommendations. However, it does not fully specify the exact structure of the response object, leaving some ambiguity. Still, it provides sufficient information for an agent to use the tool effectively.

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?

While the input schema already has 100% coverage with descriptions, the tool description adds significant meaning: it explains the two modes (trending_scan with no args, event mode, topic mode), the semantics of event slugs and topic seed questions, and the internal logic (e.g., semantic anchor, partition filter). 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 the tool's purpose: finding arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It specifies the resource (Polymarket arbitrage), the method (monotonicity and partition checks), and distinguishes from sibling tools like polymarket_edges and polymarket_fill_risk by focusing on these specific arbitrage types.

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 guidance on when to use each mode: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. It also advises on alternatives: 'For custom sizing use polymarket_fill_risk'. This clearly helps the agent decide when to invoke this tool vs alternatives.

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

B3.4/5.0
Disambiguation2/5

The tool set has several near-duplicate entries (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; five polymarket_* tools), and the server name implies topography while most tools serve unrelated data lookups, making it hard to select the right tool for a task.

Naming Consistency3/5

Most tool names use snake_case and a verb-first style, but there are notable exceptions like 'datasets', 'dem', and 'forget', and the 'pipeworx' prefix is applied inconsistently (pipeworx_feedback, pipeworx_trending vs. ask_pipeworx). The pattern is readable but not fully uniform.

Tool Count2/5

With 34 tools, the count is excessive for a server named Opentopography, especially since only 3 tools (datasets, dem, point_elevation) relate to the implied domain. The bulk of tools belong to a general-purpose data and prediction-market service, creating a severe scope mismatch.

Completeness2/5

For the implied topography domain, the surface is severely incomplete: only dataset listing, a raster fetch, and a point elevation lookup are present, missing expected operations like elevation profiles, point cloud access, or data processing. For the broader Pipeworx domain, coverage is broad but this does not match the server's stated focus.

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