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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?

Beyond readOnly/idempotent annotations, the description discloses mode-specific walk-the-ladder behavior, return fields, defaults, and risk: partial basket fills 'convert an arb into an unhedged directional position' and it names forced_directional_risk. No contradiction with the provided 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 text is long but tightly organized with SINGLE-MARKET/BASKET sections and a USE THIS directive. Each sentence conveys necessary operational detail, and the most important purpose is front-loaded.

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 two modes, no output schema, and safety-critical use case, the description is remarkably complete. It lists all return fields per mode, explains parameter interpretation, and covers edge cases like thin legs and forced directional risk, leaving little ambiguity for correct invocation.

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 coverage is 100%, the description adds essential meaning: size_usd means 'max spend on buys, target proceeds on sells' in single-market but 'settlement notional S' in basket; side has 'auto' behavior in basket; and market/event are explicitly mutually required. This materially supplements 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 purpose: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It clearly distinguishes from siblings by naming polymarket_arbitrage and polymarket_edges as signals this tool preflights, and enumerates distinct single-market and basket behaviors.

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 instructs 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains why and warns about partial basket fills becoming unhedged positions, giving clear situational guidance.

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

A3.5/5.0
Disambiguation2/5

Many tools overlap in purpose: ask_pipeworx and ask_pipeworx_beta are identical, while ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve as query/entry-point tools. The two tax-specific tools are distinct, but the sheer number of generic data-access tools makes it difficult for an agent to select the right one.

Naming Consistency2/5

Naming is a mix of snake_case (ask_pipeworx, tax_search), camelCase (ask_pipeworx_beta, compare_entities, discover_tools), and inconsistent verb styles (resolve_entity vs entity_profile vs scan_competitor_ai_presence). No clear pattern is discernible.

Tool Count1/5

The server is named 'Tax Regulations' but only 2 of 33 tools are tax-related. The other 31 tools are unrelated Pipeworx data-access, memory, subscription, and Polymarket tools, making the count wildly excessive and mismatched with the apparent purpose.

Completeness3/5

For the tax regulation domain, tax_search and tax_regulation cover keyword discovery and full-text retrieval, which is a functional core. However, the set lacks any other tax-specific operations (e.g., updates, comparisons, planning), and the majority of the tool surface is irrelevant to the stated server purpose, leaving notable gaps for an agent expecting a coherent tax toolset.