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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint), the description details behavior: walking the ladder, returning specific fields, explaining basket mode logic, and warning about forced directional risk. 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?

Structured with clear sections (SINGLE-MARKET, BASKET) and front-loaded key use case. Though dense, every sentence adds value. Slightly longer than necessary but remains effective.

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 no output schema, the description comprehensively lists return fields for both modes (e.g., top_of_book, vwap_fill_price, capture_ratio, forced_directional_risk). Explains logic and risks, making it fully self-contained.

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%, yet the description adds meaning: defaults for side and size_usd, interpretation of size_usd as max spend or target proceeds for single-market, and settlement notional for basket. Explains auto-derivation of side for 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 defines the tool as a 'Realizable-vs-theoretical edge check against live CLOB order-book depth', with specific modes for single-market and basket. It distinguishes itself from sibling tools like polymarket_arbitrage and polymarket_edges by specifying its role as a pre-check.

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?

Explicit guidance: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. Also explains why and when not to use (small trades under $500), and the risks of partial fills.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., three versions of ask_pipeworx for similar tasks, and several research/analysis tools (bet_research, deep_research, entity_profile) with unclear boundaries. The mix of Europeana-specific tools with a broad research toolkit creates confusion.

Naming Consistency2/5

Tool names are inconsistent, mixing snake_case (ai_visibility_check, ask_pipeworx), verb_noun patterns (compare_entities, resolve_entity), and short names (search, record, forget). No clear naming convention is followed throughout the set.

Tool Count2/5

33 tools is excessive for a Europeana-focused server, as only 3 tools (search, record, search_within) are directly related to Europeana. The rest are a broad, unrelated toolkit, making the server feel like a kitchen sink rather than a cohesive collection.

Completeness2/5

The Europeana-specific tool surface is severely incomplete, lacking browse collections, advanced filters, or entity linking. The inclusion of many unrelated tools does not compensate for the gaps in the core domain, resulting in a poorly scoped offering.