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Arcgis Lacounty

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

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description adds deep behavioral detail: walks the ladder, returns verdict clean|degraded|cannot_fill, warns about thin_legs and forced_directional_risk. It does not contradict annotations and meaningfully extends them by highlighting the dominant loss mode in real arb-bot P&L.

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 and structured with clear sections (SINGLE-MARKET, BASKET) and front-loaded definition. Every sentence carries information, but the paragraph is long and might overwhelm an agent scanning for quick details. Still, the complexity justifies the length, so it earns a solid 4.

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?

Despite having no output schema, the description enumerates all returned fields for both modes (top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, verdict; theoretical_sum, realizable_sum, capture_ratio, profit_usd, per-leg fill detail, thin_legs[], max_clean_notional_usd, forced_directional_risk). It also covers edge cases like partial fills and unhedged risk, making it fully complete for the tool's complexity.

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 coverage is 100%, so baseline is 3, but the description adds crucial semantic distinctions: size_usd is 'max spend on buys, target proceeds on sells' in single-market vs 'settlement notional' in basket; side behavior differs (auto-detect in basket based on partition sum). This goes beyond schema field descriptions and clarifies the mode-dependent interplay.

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: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It clearly distinguishes from siblings like polymarket_arbitrage and polymarket_edges by positioning itself as a pre-trade risk check, and it defines both single-market and basket modes with distinct outputs.

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 gives explicit usage instructions: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains why (partial fills convert an arb into unhedged directional position), providing strong context and alternative differentiation.

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

A3.7/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all handle natural-language data queries, with ask_pipeworx_beta currently identical to ask_pipeworx. discover_tools and suggest_questions both exist to help agents find tools, and the five Polymarket tools have subtle, hard-to-distinguish boundaries. Agents will frequently select the wrong tool without careful reading.

Naming Consistency4/5

Tool names are mostly lowercase snake_case with verb-noun structure (query_layer, search_datasets, resolve_entity), which is consistent and readable. However, some names break the pattern (entity_profile, layer_info, recent_changes, pipeworx_feedback) and the prefixes are not uniform. Still, the convention is predictable enough to navigate.

Tool Count2/5

34 tools is a heavy count, and the vast majority are unrelated to the server's stated 'Arcgis Lacounty' purpose. Only three tools (search_datasets, query_layer, layer_info) serve the named GIS domain, while the rest form a sprawling collection of data-lookup, prediction-market, and utility tools. This is a severe scope mismatch.

Completeness1/5

The tool surface is severely incomplete for an ArcGIS LA County server: no layer listing beyond keyword search, no metadata endpoints, no editing, no spatial operations. The broader tool set lacks a coherent domain, making coverage impossible to assess beyond noting the glaring absence of core GIS functionality.

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