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Arcgis Pittsburgh

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

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and non-destructive, and the description adds substantial behavioral detail: mode requirements, default behaviors, return fields (top_of_book, vwap_fill_price, slippage_pp, etc.), and the risk of forced_directional_risk. No contradiction.

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 highly information-dense, covering two operating modes, parameter defaults, output fields, and risk guidance. It is structured with clear mode markers (SINGLE-MARKET, BASKET) and starts with the core purpose, so it earns a 4 rather than 5 for being somewhat lengthy.

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 there is no output schema, the description enumerates all relevant return fields for both modes and explains the use case. It also addresses edge cases like thin books and partial fills, making it remarkably complete.

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% with detailed parameter descriptions. The description adds extra depth by explaining the intent of each side (e.g., sell_yes = capture overround, buy_yes = capture underround) and clarifying size_usd interpretation in basket mode as settlement notional per leg. This goes 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 clearly states the tool performs a 'Realizable-vs-theoretical edge check against live CLOB order-book depth' and distinguishes between single-market and basket modes. It explicitly references sibling tools (polymarket_arbitrage, polymarket_edges), making its unique purpose clear.

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: '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 fills converting arb into 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

B3.4/5.0
Disambiguation2/5

Several near-duplicate tool clusters exist: ask_pipeworx, ask_pipeworx_beta (explicitly identical right now), and ask_pipeworx_grounded overlap heavily, as do polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread. The three ArcGIS tools (search_datasets, layer_info, query_layer) are distinct, but their purpose is drowned out by the unrelated Pipeworx data tools.

Naming Consistency2/5

Most names use snake_case, but the pattern is inconsistent: some are verb_noun (ask_pipeworx, search_datasets, resolve_entity), some are noun_noun (layer_info, entity_profile, pipeworx_feedback), and some are adjective_noun (recent_alerts, recent_changes). Verbs are also inconsistent across similar actions (scan_ vs check_ vs compare_, and three different polymarket_ verbs plus a bare bet_research).

Tool Count1/5

34 tools is already heavy, but the server is named Arcgis Pittsburgh and only 3 of the 34 tools relate to Pittsburgh GIS data; the other 31 belong to unrelated domains (Pipeworx data lookup, prediction markets, memory, npm auditing). This is an extreme scope mismatch — the tool count is far too high for the stated purpose and mostly irrelevant noise.

Completeness2/5

For the ArcGIS Pittsburgh domain, the surface has basic read coverage (search datasets, inspect layer schema, query records) but no update/delete/write operations and no geospatial analysis tools, which are significant gaps for a GIS server. The broader tool set is a grab bag of research, prediction-market, and memory features that don't form a coherent lifecycle for any single domain, so completeness cannot be assessed as a unified surface.

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