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Thesportsdb

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 already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds significant behavioral context: it walks the ladder, returns specific fields (top_of_book, vwap_fill_price, slippage_pp, etc.), explains basket mechanics, and cautions about forced directional risk. No contradictions with 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 dense with information but front-loaded with the core purpose and mode breakdown. While slightly verbose, every sentence earns its place. Capitalization and bullet-like formatting aid readability. Minor room for tighter phrasing.

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?

With 4 parameters, no output schema, and complex dual-mode behavior, the description thoroughly covers both modes, required parameters, defaults, output fields, and risk scenarios. It leaves no critical ambiguity for correct usage.

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 description coverage is 100%, but the description adds essential meaning: clarifies size_usd interpretation differs per mode, side auto-detection in basket mode, and that one of market or event is required. Also provides defaults and clamp ranges, going beyond 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', distinguishing between single-market and basket modes. It explicitly relates to sibling tools like polymarket_arbitrage and polymarket_edges, making its unique purpose evident.

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?

Provides explicit when-to-use instructions: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. Also warns about theoretical overround not being capturable and partial basket fill risks, guiding against misuse.

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

B3.3/5.0
Disambiguation2/5

The sports tools are distinct, but the majority of the set has heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve as query/entry-point tools, with ask_pipeworx and ask_pipeworx_beta explicitly identical. The Polymarket family (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) also blurs together.

Naming Consistency2/5

The sports subset follows a clean verb_noun pattern (get_player, list_leagues, search_teams), but the rest mixes several naming schemes: ask_pipeworx*, pipeworx_* prefixed tools, polymarket_* tools, one-word verbs (remember, recall, forget), and compound names like scan_competitor_ai_presence. No single consistent convention governs the set.

Tool Count2/5

42 tools is far too many for a server named Thesportsdb; only 10 tools relate to sports data, while 32 belong to an unrelated Pipeworx data/betting/memory platform. The set feels like two or three servers merged into one, making it heavy and unfocused for any single purpose.

Completeness2/5

For the stated sports domain, the surface is partial: you can get teams, players, league tables, and recent/next fixtures, but there are no player statistics, head-to-head records, venue details, or season history — leaving notable gaps. The Pipeworx half is broad but doesn't belong in a server with this name, so the set as a whole is incomplete for its apparent purpose.

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