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Arcgis Lubbock

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

A5/5.0
Behavior5/5

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

Annotations declare read-only and non-destructive, and the description adds behavior beyond that: it 'walks the ladder', interprets size_usd differently per mode, and discloses the risk of partial basket fills converting arbs into unhedged directional positions. It also lists return fields, giving the agent an accurate model of tool behavior. No contradiction 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.

Conciseness5/5

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

The description is long but every sentence earns its place. It is structured with clear sections (SINGLE-MARKET, BASKET) and enumerates return values and defaults. Despite the length, it is dense and information-dense with no fluff, making it an effective reference for a complex tool.

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, multiple return fields, risk warnings), the description is thorough. There is no output schema, so the description carries the full burden of conveying return values and semantics, and it does so comprehensively, covering edge cases like thin legs and forced directional risk. It also addresses when to use it relative to alternatives.

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 description coverage is 100%, the description adds significant meaning: it explains the 'one of market or event' requirement, side defaults and how size_usd is interpreted differently in single-market (max spend/target proceeds) vs basket (settlement notional shares per leg). These semantics are not in the schema and are critical for correct invocation.

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 specific verb and resource: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It clearly distinguishes from siblings like polymarket_arbitrage and polymarket_edges by focusing on fill risk and slippage. The two modes (single-market and basket) are explicitly defined, leaving no ambiguity about what the tool does.

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 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 the distinction between single-market and basket modes and why partial fills are dangerous, effectively contrasting with alternatives and giving clear context for selection.

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
Disambiguation2/5

Many tools overlap in purpose, particularly the ask_pipeworx variants (stable, beta, grounded) and deep_research, making it difficult for an agent to choose correctly. Additionally, the Arcgis-specific tools are buried under numerous general Pipeworx tools.

Naming Consistency4/5

Most tools follow a verb_noun pattern (e.g., ask_pipeworx, compare_entities), but there are minor inconsistencies like ai_visibility_check vs scan_competitor_ai_presence and the simpler Arcgis tool names.

Tool Count2/5

With 34 tools, the server is overloaded, especially since the majority are Pipeworx meta-tools unrelated to the Arcgis Lubbock purpose. A well-scoped ArcGIS server would have far fewer tools.

Completeness2/5

For an ArcGIS server, only three tools directly serve that purpose (search_datasets, layer_info, query_layer), lacking editing, analysis, or visualization capabilities. The remaining tools address a completely different domain.

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