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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

A4.8/5.0
Behavior5/5

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

Annotations already show readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds behavioral context about forced directional risk, thin legs, and the dominant loss mode, without contradicting 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 lengthy but well-structured with clear sections for single-market and basket modes. Each sentence adds value, though minor redundancy exists (e.g., repeating 'default 1000').

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?

For a tool with 4 params, no output schema, and high complexity (CLOB depth, basket mode), the description thoroughly explains return fields, edge cases, and safety warnings, making it complete.

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%, baseline 3. The description adds meaning by explaining modes (single-market vs basket), default auto detection for basket side, and interpretation of size_usd for both modes, justifying a 4.

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 with specific verbs and resource names.

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 states when to use: 'before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. Also warns about risks of thin books and partial fills, providing clear context.

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

A3.7/5.0
Disambiguation2/5

Several tool groups have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges / polymarket_arbitrage / polymarket_edge_tracker / polymarket_fill_risk / polymarket_kalshi_spread / bet_research all push prediction-market opportunities and can be confused, and ai_visibility_check is nested inside scan_competitor_ai_presence. discover_tools and suggest_questions also overlap as tool-discovery entry points.

Naming Consistency3/5

Everything is snake_case and mostly descriptive, but conventions are mixed: verb-first names (resolve_entity, validate_claim, compare_entities, search_within) sit beside noun-first names (entity_profile, recent_changes, bet_research, polymarket_edges), and brand-prefixed tools (pipeworx_feedback, pipeworx_trending) have unprefixed functional siblings (list_subscriptions, recent_alerts). The two actual Base64 tools (base64_encode, base64_decode) don't match the dominant Pipeworx naming style at all.

Tool Count2/5

33 tools is heavy for any single server, and the mismatch is extreme: the server is named 'Base64' yet only 2 of 33 tools relate to encoding/decoding — the other 31 form a sprawling data-research platform. Even judged as a data platform, the count exceeds the comfortable range and includes near-duplicates (the ask_pipeworx family, the Polymarket family).

Completeness4/5

The factual-data surface is well covered: query, grounded lookup, deep research, entity profiling, comparison, claim verification, entity resolution, subscriptions (subscribe/list/unsubscribe/recent_alerts), memory (remember/recall/forget), feedback, and tool discovery all exist with no obvious dead ends. The Base64 encoding domain is also complete (encode/decode across four variants). Minor gaps exist (e.g., no way to update a profile or edit memory entries) but they're workable.