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Arcgis Princewilliam

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

A4.9/5.0
Behavior5/5

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

The description goes far beyond the annotations. It discloses thresholds (3pp, 0.30 Jaccard, >20% placeholder), explains the partition_sum check, the fill verification with CLOB depth, and warns 'do not trade it' when realizable_edge ≤ 0. It also explains the semantic anchor and skipped_low_similarity. No contradiction with readOnlyHint=true.

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 lengthy but well-structured with labeled sections (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK) and front-loaded purpose. Every sentence conveys needed operational detail for a complex two-mode tool. Slightly verbose but not wasteful; earns its length.

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 (two modes, fill check, multiple thresholds) and no output schema, the description covers all essential aspects: return fields, edge cases, safety checks, and cross-mode behavior. It is complete enough for an agent to invoke correctly and interpret results.

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 schema coverage is 100%, the description adds significant semantic value: event expects slugs or full URLs, topic expects seed questions, and it explains how each mode behaves beyond the schema descriptions. It also describes response details per mode, adding meaning not present in the input schema alone.

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?

Starts with a clear verb+resource: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It distinguishes itself from sibling tools like polymarket_edges and polymarket_fill_risk by specifying its unique arbitrage-detection mechanism and mentioning 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?

Provides explicit mode selection: no args for trending_scan, event for a specific market, topic for cross-event scanning. It recommends event for specific markets, gives concrete examples, and even points to polymarket_fill_risk for custom sizing. This is exactly the kind of when-to-use alternative guidance desired.

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

A3.7/5.0
Disambiguation3/5

The set mixes several overlapping clusters: three ask_pipeworx variants (beta is explicitly identical to stable right now), six Polymarket tools with similar opportunity-scanning purposes, and two AI-visibility tools that duplicate each other. However, the descriptions are detailed enough that an agent can usually pick correctly, so the ambiguity is moderate rather than severe.

Naming Consistency2/5

Tool names follow no single convention — some are verb_noun (query_layer, validate_claim), some noun_noun (entity_profile, layer_info), some company-prefixed clusters (pipeworx_*, polymarket_*), and a few standalone verbs (forget, recall). While snake_case is consistent, the absence of a uniform verb_noun pattern across the set makes it unpredictable.

Tool Count2/5

At 34 tools, the server is oversized for its apparent purpose, and the count is even more problematic because most tools belong to a general Pipeworx/data platform while only 3 serve the 'Arcgis Princewilliam' GIS theme. The set feels like two unrelated servers merged, with many tools earning no clear place in a unified product.

Completeness2/5

The GIS side is a read-only stub (search, schema, and query) with no editing or feature-level retrieval, and the broader Pipeworx side has a notable dead end: tools return pipeworx:// citation URIs but no tool is provided to fetch those resources. The result is a surface that is simultaneously over-built in prediction markets and under-built in its namesake domain.

Resources