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Arcgis Washingtoncomn

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?

Annotations already declare readOnly/openWorld/idempotent, but the description adds rich behavioral context: Jaccard similarity threshold, partition placeholder filter, fill check against live CLOB depth, and explicit 'do not trade it' when realizable edge ≤ 0. No contradictions with annotations; this exceeds the baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is long but structured with clear section headers (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK) and front-loaded with the main purpose. Every sentence adds value: mode selection, thresholds, response fields, and trading warnings. This is appropriate for a multi-mode tool with such detailed behavior.

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?

The description is highly complete for a complex tool: it explains all inputs, output structures (opportunities[], partition_check, fill_check fields), safety filters, and even when to delegate to polymarket_fill_risk. Since there is no output schema, this detailed textual description fully compensates and equips the agent to invoke and interpret results 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?

Schema coverage is 100% and both 'event' and 'topic' have descriptions, so baseline is 3. The tool description goes beyond schema with examples (like 'fed-decision-may-2026'), notes that full URLs are accepted, and explains the semantic difference between the two modes (single-event vs cross-event). This adds meaningful context but the schema already carried the primary definitions.

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 opens with a clear verb+resource+method: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It then distinguishes three modes (trending_scan, event, topic), which separates this from sibling tools like polymarket_edges and 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?

Explicitly states when to use each mode: 'Call with NO args for a trending_scan', 'pass event for the strongest per-event partition_check', 'topic for a themed cross-event scan'. It also recommends event for specific markets and points to polymarket_fill_risk for custom sizing, clearly guiding the agent to 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

A3.8/5.0
Disambiguation3/5

The ArcGIS tools (query_layer, layer_info, search_datasets) are clearly distinct, but the Pipeworx family has heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools can all appear as plausible entry points for a similar data lookup task. The memory and subscription tools are well separated, but the router-style tools create real ambiguity.

Naming Consistency4/5

Almost all tools use lowercase snake_case names with a verb-first pattern (ask_pipeworx, query_layer, subscribe, remember) or clear noun descriptors (entity_profile, layer_info, polymarket_edges). A few names are more cryptic (recall, forget, resolve_entity) but they still follow the same style. No mixed camelCase or inconsistent separators.

Tool Count2/5

34 tools is well beyond what the apparent ArcGIS Washington County purpose needs; only three tools actually concern GIS data. The rest are a broad Pipeworx research suite, memory, subscriptions, feedback, and AI-visibility probes. This makes the surface feel like two or three unrelated servers grafted together rather than one scoped package.

Completeness3/5

For the ArcGIS slice, you can discover, inspect, and query layers, but there is no write or create capability, no field-wise editing, no map/feature export, and no feature-level CRUD. The Pipeworx data side is more comprehensive, but the overall server confuses its purpose. The mixed-domain coverage leaves the GIS part only a thin slice of the offered features.

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