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Arcgis Sanjose

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 adds significant behavioral context beyond the annotations (which already indicate safe, read-only, idempotent operation). It details the algorithmic approach (monotonicity violations, partition-sum checks), scanning scope (top 200 markets by weekly volume), semantic anchor constraints (Jaccard similarity ≥0.30), partition filter for placeholders, and fill check logic with tradeability warnings. 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 front-loaded with the core purpose and mode options, then dives into details like semantic anchor, partition filter, and fill check. It is informative but somewhat verbose at ~350 words; some sentences could be tightened. However, the structure is logical and easy to follow, using colons and punctuation to separate concepts.

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 optional parameters, no required, no output schema), the description fully covers invocation, expected outputs (opportunities[] with fields, partition_check structure, fill check details), and edge cases (placeholder filtering, low similarity skipping). The agent has all needed information to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While the input schema already provides descriptions for both parameters with 100% coverage, the description adds substantial meaning by giving concrete examples (e.g., 'fed-decision-may-2026' for event, 'Strait of Hormuz traffic returns to normal' for topic) and explaining the behavioral differences between the two modes. It also clarifies that full Polymarket 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's purpose: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It distinguishes between three modes (no args, event, topic) and explains what each does, differentiating 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 provides explicit guidance on when to use each mode: 'Call with NO args for a trending_scan... pass event for the strongest per-event partition_check, or topic for a themed cross-event scan.' It explains that event mode is recommended for a specific market, topic catches cross-event patterns, and includes fill check warnings and reference to 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

A3.8/5.0
Disambiguation3/5

While many tools have distinct purposes, there is overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as multiple Polymarket and entity-related tools. Descriptions are detailed but could confuse agents on which tool to use for a specific query.

Naming Consistency3/5

Most tool names use snake_case and many start with verbs, but there is inconsistency with noun-starting names like entity_profile, layer_info, and pipeworx_feedback. No strong verb_noun or other consistent pattern across the set.

Tool Count3/5

With 33 tools, the count is relatively high but could be justified for a broad data platform. However, given the server name 'Arcgis Sanjose', the number seems excessive as most tools are unrelated to ArcGIS geospatial functions.

Completeness2/5

The tool set is severely incomplete for the implied ArcGIS San Jose domain, with only 3 tools (search_datasets, layer_info, query_layer) supporting that purpose. The rest are from the Pipeworx ecosystem, creating a mismatch between server name and actual functionality.

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