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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

A4.8/5.0
Behavior5/5

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

Annotations provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint = false. The description adds behavioral context: walks the ladder, returns verdicts (clean/degraded/cannot_fill), forced directional risk, and the dominant loss mode (partial basket fills). No contradiction 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?

Description is a single long paragraph but effectively front-loaded with purpose and requirements. Could be more structured (e.g., bullet points for modes), but each sentence provides necessary information. Not overly verbose 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 covers both modes, default behaviors, return fields (top_of_book, vwap_fill_price, slippage, verdict, etc.), and risks. It is complete enough for an AI to understand and invoke the tool correctly.

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 description coverage is 100%, so baseline is high. The description adds operational details: default side for basket is auto from partition sum, size_usd interpreted as settlement notional in basket mode, clamp 10–1,000,000. Adds meaning 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 it is a 'realizable-vs-theoretical edge check against live CLOB order-book depth,' specifying two modes (single-market and basket) and listing specific return fields. It distinguishes from sibling tools like polymarket_arbitrage and polymarket_edges.

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 to use before acting on polymarket_arbitrage sell/buy-every-leg signals or polymarket_edges trades above ~$500, explaining why (theoretical overround not capturable on thin books, partial fills create unhedged positions). Also states the prerequisite of providing either market or event.

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

A3.8/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx_beta is explicitly identical to ask_pipeworx, and discover_tools/suggest_questions plus entity_profile/recent_changes/compare_entities/validate_claim overlap in purpose. An agent selecting among the five ask/deep-research variants or six Polymarket tools will frequently need to read lengthy descriptions to avoid picking the wrong one.

Naming Consistency3/5

Most names are readable snake_case and clear verb_noun phrases like search_articles, resolve_entity, and validate_claim, with helpful families like polymarket_* and timeline_*. However, several tools are bare noun phrases (entity_profile, recent_alerts, pipeworx_trending, tone_distribution), and the memory trio (remember/recall/forget) breaks the domain-prefix pattern.

Tool Count2/5

35 tools is past the 25+ threshold and feels bloated for a server nominally about GDELT; much of the surface is meta/utility tooling (diagnostics, memory, discovery, subscriptions) rather than core news retrieval. Several tools could be consolidated, such as ask_pipeworx_beta and the multiple Polymarket edge/arb/research variants.

Completeness4/5

For its broad data/news/prediction-market scope, the surface is quite complete: GDELT search, volume, tone, and distribution are covered, along with entity resolution, company profiles, comparisons, claim verification, and trade-side analytics. Minor gaps exist, such as no full-text article fetch or direct GDELT raw-event export, but agents can mostly work around them.

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