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Regulatory Catalysts

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?

The description adds significant behavioral context beyond annotations: it explains that the tool walks the order book ladder, returns verdicts (clean|degraded|cannot_fill), and for baskets warns about forced directional risk and thin_legs. It is consistent with readOnlyHint and idempotentHint 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 front-loaded with the core purpose and well-structured with sections for requirements, single-market, and basket. It is slightly verbose but every sentence adds value, especially given the tool's complexity.

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 no output schema, the description thoroughly explains return fields for both modes (top_of_book, vwap_fill_price, slippage_pp, verdict for single-market; theoretical_sum, realizable_sum, capture_ratio, profit_usd, thin_legs, forced_directional_risk for baskets). It covers edge cases and rationale.

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%, and the description adds extra meaning: default values (side default, size_usd default), interpretations of size_usd (max spend for buys, target proceeds for sells; settlement notional for baskets), and the auto-detection logic for side in basket mode.

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 it is a 'Realizable-vs-theoretical edge check against live CLOB order-book depth' and explicitly differentiates from sibling tools like polymarket_arbitrage and polymarket_edges by specifying when to use it before acting on arb signals or trades above ~$500.

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 guidance on when to use the tool: '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 is not capturable on thin books and how partial fills convert arb to directional position.

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
Disambiguation4/5

Most tools have distinct purposes, but the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and multiple Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, etc.) could cause confusion for an agent selecting the appropriate tool.

Naming Consistency2/5

Tool names mix snake_case and camelCase inconsistently, with no strong verb_noun pattern. Examples include 'ask_pipeworx' vs 'discover_tools' vs 'validate_claim', indicating a lack of naming convention.

Tool Count2/5

33 tools is high for a single server, including many utility tools (memory, subscriptions) that seem peripheral to the core regulatory/data domain. This suggests scope creep and could overwhelm agents.

Completeness4/5

The tool set covers a wide range of regulatory and financial data needs, including company profiles, entity comparison, claim validation, FDA catalysts, and prediction market analysis. Minor gaps exist (e.g., no tool for editing data), but overall it is comprehensive for its stated purpose.

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