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Arcgis Maricopa

by io.github.pipeworx-io

Polymarket Fill Risk

polymarket_fill_risk
Read-onlyIdempotent

Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of market (single-market mode) or event (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideNoSingle-market: buy_yes | sell_yes | buy_no | sell_no (default buy_yes). Basket: sell_yes | buy_yes (default auto — sell if partition sum > 1, buy if < 1).
eventNoBasket mode: event slug or full polymarket.com URL — checks every leg of the partition.
marketNoSingle-market mode: market slug or full polymarket.com URL.
size_usdNoSingle-market: USD to spend (buys) or target proceeds (sells). Basket: settlement notional — shares per leg, each paying $1 at resolution. Default 1000, clamp 10–1,000,000.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, all consistent with the description. The description adds significant behavioral context, such as walking the order-book ladder, returning verdict categories (clean|degraded|cannot_fill), and warning about forced directional risk and partial fills.

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 clear sections for SINGLE-MARKET and BASKET modes. Every sentence adds informative value given the tool's complexity, though a slightly tighter structure could improve readability.

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?

With no output schema, the description fully enumerates all return fields (e.g., top_of_book, vwap_fill_price, slippage_pp, capture_ratio, thin_legs, forced_directional_risk) and explains edge cases and risk profiles. It also covers mode-specific behavior, making it a complete reference for the agent.

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?

Although the schema covers 100% of parameters, the description adds crucial semantics: it explains the two modes (single-market vs basket), how size_usd is interpreted differently in each mode, and the default auto behavior for side in basket mode. This goes beyond the schema's basic 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 identifies the tool as a 'Realizable-vs-theoretical edge check against live CLOB order-book depth,' which is a specific verb-resource combination. It distinguishes itself from sibling tools like polymarket_arbitrage and polymarket_edges by focusing on fill risk and slippage.

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 explicitly states when to use the tool: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains why, citing the risk of partial basket fills and unhedged directional positions.

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

Many tools have distinct purposes, but there is overlap within the Pipeworx family (ask_pipeworx vs ask_pipeworx_grounded) and Polymarket tools (bet_research, polymarket_edges, etc.). Descriptions are detailed and help differentiate, but the sheer number of tools from different domains can cause an agent to select the wrong one for a given task.

Naming Consistency2/5

Naming is highly inconsistent: some tools follow verb_noun (ask_pipeworx, compare_entities), others are nouns (layer_info, entity_profile), and some have prefixes (pipeworx_trending, polymarket_arbitrage). There is no uniform pattern, making the set feel chaotic.

Tool Count2/5

33 tools is far too many for a server named 'Arcgis Maricopa', which only has 3 GIS-specific tools. The remaining tools are from unrelated domains (polymarket betting, general Pipeworx queries, utilities), making the tool set bloated and unfocused for its stated purpose.

Completeness3/5

For the ArcGIS domain, the set is minimal (only search, schema, and query) and lacks management or analysis tools. However, the broader toolset covers many data domains (finance, drugs, prediction markets), but with gaps like no update/delete operations for the GIS data. The overall coverage is mixed.

Resources