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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

A4.9/5.0
Behavior5/5

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

Annotations already declare non-destructive, read-only, and idempotent behavior. The description adds crucial behavioral context: it walks the ladder, returns verdicts (clean|degraded|cannot_fill), explains forced directional risk, and mentions that partial basket fills create unhedged positions—the dominant loss mode. 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?

The description is somewhat lengthy (~150 words) but well-structured: it starts with the core purpose, then details each mode, and ends with usage guidance. While dense, every sentence contributes meaning; minor verbosity prevents a perfect score.

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 modes, multiple return fields, no output schema), the description comprehensively covers inputs, outputs (top_of_book, vwap_fill_price, slippage_pp, verdicts, per-leg details, etc.), risks, and contextual warnings. It is fully adequate for agent selection and invocation.

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% with all parameters described. The description adds value by clarifying defaults (size_usd default 1000, clamp 10–1,000,000), explaining side auto-detection in basket mode, and distinguishing market vs event modes 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's purpose: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It distinguishes two modes (single-market and basket) and explicitly differentiates from siblings like polymarket_arbitrage and polymarket_edges by stating when to use this tool before acting on those signals.

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 guidance: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' Also warns about the risk of partial fills converting an arb into an unhedged directional position, giving clear when-not-to-skip usage.

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

The ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded trio are nearly indistinguishable, with beta currently behaving identically to the stable version. Entity_profile, recent_changes, and compare_entities also overlap heavily as multi-source company research tools, and the six polymarket tools create additional boundary confusion.

Naming Consistency2/5

Most tools use snake_case, but there is no consistent verb_noun pattern: some are imperative phrases (ask_pipeworx, bls_get_series, resolve_entity), while others are noun phrases (entity_profile, pipeworx_feedback, polymarket_edges, recent_alerts). Even within the bls_* family, bls_latest breaks the verb pattern established by bls_get_series and bls_search.

Tool Count2/5

35 tools is well above the 25+ threshold for 'too many', and the server is named Bls yet only four tools actually serve BLS data. Most of the remaining tools cover unrelated domains like Polymarket arbitrage, memory, feedback, and general Pipeworx routing, making the count feel inflated for the apparent purpose.

Completeness3/5

The four BLS-specific tools cover search, browse, historical series fetch, and latest value, but there is no multi-series fetch or series metadata detail, which is a notable gap for a BLS-focused server. The broader Pipeworx toolset is extensive, but the lack of a coherent stated domain makes completeness hard to evaluate as a unified surface.