Skip to main content
Glama

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 mark it as read-only, open-world, idempotent, non-destructive. Description adds rich behavioral details: walks order-book ladder, returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, verdict. In basket mode, returns theoretical_sum vs realizable_sum, capture_ratio, profit_usd, thin_legs, max_clean_notional_usd, forced_directional_risk. Alerts about risks of partial fills. No contradictions 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 comprehensive but somewhat lengthy; however, every sentence provides necessary information. Structure with sections (SINGLE-MARKET, BASKET) improves readability. Could be slightly more concise but justified given 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?

Given the tool's complexity (two modes, risk assessment), no output schema, and well-defined annotations, the description covers all necessary aspects: purpose, parameters, return values, usage context, and risk warnings. No gaps identified.

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%, but schema descriptions are minimal. The tool description adds significant meaning: explains side defaults per mode, clarifies size_usd interpretation vary by mode (spend vs target proceeds vs settlement notional), and emphasizes that market and event are mutually exclusive. Adds value 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?

Description clearly states it checks realizable-vs-theoretical edge against live CLOB order-book depth, with explicit separation into single-market and basket modes. It distinguishes itself from sibling tools like polymarket_arbitrage and polymarket_edges by specifying its role as a pre-execution check. Specific verb+resource+scope.

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 this tool before acting on certain signals from polymarket_arbitrage and polymarket_edges, and provides a threshold (~$500). Explains why: theoretical overround on thin books is not capturable, and partial basket fills convert arb into directional position. Clear when-to-use and when-not-to-use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation3/5

Most tools have distinct purposes and the descriptions are unusually thorough, but ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and several discovery/prediction-market tools (polymarket_edges vs polymarket_arbitrage, discover_tools vs suggest_questions) occupy overlapping territory. An agent could reasonably route to the wrong variant despite the documentation.

Naming Consistency4/5

The dominant convention is lowercase snake_case with a leading verb (ask_pipeworx, list_subscriptions, validate_claim, resolve_entity), which makes the set predictable. A few noun-first outliers like pipeworx_trending, recent_alerts, and polymarket_edge_tracker are minor deviations rather than a broken pattern.

Tool Count2/5

34 tools is well above the coherence sweet spot for an MCP server, and much of that count is made up of meta-wrappers and convenience variants around the same Pipeworx router. The broad scope explains some of the count, but the surface still feels heavy for a single named server.

Completeness3/5

The Pipeworx side is very complete: lookups, grounded verification, research, entity profiles, comparisons, prediction-market fill checks, subscriptions, and memory all have lifecycle coverage. However, the server is named Obis and only find_occurrences, get_statistics, and get_taxon serve that domain, leaving obvious marine-biodiversity operations like occurrence detail, dataset listing, and download paths missing.