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Tradier

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 mark the tool as read-only, idempotent, and non-destructive. The description adds substantial behavioral context beyond annotations: it explains basket fill risks (thin legs, forced directional risk), return fields (verdict, capture_ratio, max_clean_notional), and the dominant loss mode from partial fills. This is rich context, though the density slightly reduces clarity.

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 but not wasteful; every sentence adds unique information. It front-loads the core purpose and mode distinction. However, the length (especially the basket detail) could be more structured (e.g., using bullet points) to improve scannability while maintaining completeness.

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 complexity (two operation modes, financial risk implications, no output schema), the description is remarkably complete. It enumerates all key return fields (top_of_book, vwap_fill_price, slippage, per-leg fill detail, verdict, etc.) and explains failure modes. The agent has sufficient information to understand outputs and risks.

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%, so baseline is 3. The description adds value by clarifying the interpretation of size_usd (spend vs target proceeds for single-market, settlement notional for basket) and explaining the auto side logic for baskets. This goes beyond the schema's descriptions, justifying a higher score.

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', identifies two distinct modes (single-market and basket), and distinguishes itself from sibling tools like polymarket_arbitrage and polymarket_edges by focusing on fill feasibility rather than signal generation.

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?

Explicit when-to-use guidance is provided: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. It also explains why (theoretical overround on thin books, partial fills converting arb to directional risk), effectively steering the agent toward this tool and away from alternatives.

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

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools all serve general data querying, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_edge_tracker all target prediction-market opportunities. An agent would struggle to pick the right one consistently despite long descriptions.

Naming Consistency2/5

Naming conventions are mixed: some tools use snake_case bare verbs (remember, recall, forget), some use a pipeworx_ prefix, some use tradier_ prefix, and some use descriptive phrases (generate_llms_txt, scan_competitor_ai_presence). There is no consistent verb_noun or prefix pattern across the set.

Tool Count2/5

34 tools is on the heavy side, but more importantly the count does not match the server's stated identity. The server is named Tradier, yet only 3 of 34 tools are Tradier-specific market data tools; the rest are Pipeworx research, prediction-market, memory, and subscription utilities. The scope feels bloated and unfocused.

Completeness1/5

For a server named Tradier, the surface is severely incomplete: only quote, option expirations, and option chain are provided. Missing are account info, positions, orders, historical data, watchlists, and other core brokerage/trading operations. The Pipeworx research side is broad, but the apparent trading domain has major gaps that would cause agent failures.

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