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Arcgis Orovalley

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description goes far beyond that by detailing behavior: '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),' plus basket-mode details like thin_legs and forced_directional_risk. This adds substantial behavioral context.

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 dense but well-structured, with clear mode sections (SINGLE-MARKET/BASKET) and a strong front-loaded purpose. While long, every sentence earns its place given the tool's complexity. Minor deduction for wall-of-text formatting that could benefit from bullet points, but content is efficient.

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?

For a complex two-mode tool with no output schema, the description is remarkably complete. It enumerates return fields, explains verdict values, interprets size_usd differently per mode, and warns about failure modes. The only minor omission is error handling for missing parameters, but 'REQUIRES one of' covers that. Extremely comprehensive.

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?

Schema covers 100% of parameters with basic descriptions, but the tool description enriches them: 'size_usd' is explained as 'max spend on buys, target proceeds on sells' in single market and 'settlement notional S (shares per leg)' in basket mode. It clarifies 'side' defaults per mode and the one-of requirement for market/event, adding meaning beyond the schema.

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-resource phrase: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It clearly distinguishes itself from siblings by stating 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500,' naming the exact sibling tools and use case.

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?

Usage guidance is explicit: 'USE THIS before acting on...' tells when to use, and the two modes (single-market vs basket) explain parameters and interpretation. It also provides rationale by warning that 'theoretical overround on thin books is not capturable' and that partial fills create unhedged positions, giving clear context and implied exclusions.

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

A3.9/5.0
Disambiguation3/5

The descriptions are extraordinarily detailed and genuinely differentiate most tools, but the set contains near-clones (ask_pipeworx, ask_pipeworx_beta which is explicitly 'identical' to it, and ask_pipeworx_grounded) plus five polymarket tools whose boundaries (arbitrage vs edges vs edge_tracker vs fill_risk vs kalshi_spread) overlap enough to cause misselection. An agent navigating this surface must read full descriptions to choose correctly, which defeats quick tool selection.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern (ask_pipeworx, compare_entities, resolve_entity), but there are clear deviations: bare single-word verbs (remember, recall, forget, subscribe, unsubscribe), prefix-family names (pipeworx_feedback, pipeworx_trending; polymarket_edges, polymarket_fill_risk), and a disjoint ArcGIS trio (layer_info, query_layer, search_datasets) that breaks the dominant convention. It is readable but not predictable across the whole set.

Tool Count2/5

34 tools is far beyond what the 'Arcgis Orovalley' purpose warrants — only 3 tools (search_datasets, layer_info, query_layer) actually relate to GIS, with 31 unrelated tools bolted on covering financial data, prediction markets, memory, subscriptions, and AI visibility. This is a sprawling mega-server where an agent must hold an enormous option set in mind; the surface appears to be several platforms fused together rather than one well-scoped toolset.

Completeness3/5

The genuine ArcGIS surface (search datasets → layer_info → query_layer) is a complete read-only workflow with no dead ends, and the Pipeworx side is impressively comprehensive (routing, grounded answers, research, entity, compare, resolve, validate, memory, subscriptions, feedback). But the tool set as a whole serves no single coherent domain — the declared purpose (ArcGIS Oro Valley data) lacks any write/editing operations, while the majority of the surface addresses unrelated concerns, so 'complete' only applies to one small slice of the 34 tools.

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