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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

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description focuses on behavioral details beyond safety. It describes how the tool 'walks the ladder', returns a verdict (clean|degraded|cannot_fill), and for baskets identifies 'thin_legs' and 'forced_directional_risk'. This adds meaningful context without contradicting annotations.

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 somewhat lengthy but well-structured: first sentence defines purpose, then requirements, then two detailed mode explanations, ending with usage guidance. It is front-loaded and each part earns its place given the tool's complexity (two modes). Minor redundancy could be trimmed, but overall 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 tool with no output schema and two modes, the description is highly complete. It explains return fields for both modes, usage context, and warns about partial fills and directional risk. The annotations cover safety, so the description fully fills the gaps, making it adequate for correct invocation.

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%, but the description adds significant meaning: it explains that size_usd in single-market is 'max spend on buys, target proceeds on sells', and in basket mode is 'settlement notional S (shares per leg; each share pays $1)'. It also clarifies side defaults and mode selection, adding value 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 checks 'Realizable-vs-theoretical edge against live CLOB order-book depth'. It distinguishes two modes (single-market and basket) and mentions return fields for each. It explicitly differentiates from sibling tools by stating 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500', making the tool's role distinct.

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 provides explicit when-to-use guidance: 'before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. It explains why (theoretical overround not capturable, partial fills cause unhedged positions) and implies not for small trades, giving clear context and 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
Disambiguation2/5

The tool set mixes three near-identical ask_pipeworx variants, multiple overlapping prediction-market tools (polymarket_edges, polymarket_arbitrage, bet_research), and three endoflife tools buried among 31 unrelated Pipeworx tools. This makes distinguishing between tools genuinely confusing, especially when several appear to route to the same underlying data.

Naming Consistency3/5

Most names use lowercase snake_case, but the verb-noun pattern is inconsistent: some are verb_noun (list_products, get_product), others noun_noun (polymarket_edges, bet_research), and a few are bare verbs (recall, forget). The style is readable but does not follow a single predictable convention.

Tool Count2/5

With 34 tools, the count is far too high for a server named 'Endoflife'—only three tools actually relate to endoflife.date tracking. The remaining 31 tools belong to a separate Pipeworx platform, making the tool count an extreme over-scoping for the apparent purpose.

Completeness4/5

The endoflife subset is complete: list_products, get_product, and get_cycle cover the full lifecycle of discovering and retrieving release/support timelines with no dead ends. The broader Pipeworx toolkit also appears fairly comprehensive for its own domain, but the mixed set makes it hard to assess a single coherent surface.