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Pride

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.

Schema Changelog

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

  1. Added
  2. Removed
  3. Added

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral context beyond this: it walks the order book ladder, returns specific metrics (top_of_book, vwap_fill_price, slippage_pp, shares_filled, verdict), and critically warns that partial basket fills convert an arb into an unhedged directional position. This directly augments the annotation-only safety profile with practical risk details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every sentence earns its place. It is logically structured: purpose statement, mode requirements, detailed behavior per mode, return fields, and a final usage directive. It is front-loaded with the core function and ends with an actionable 'USE THIS before...' statement. No redundancies or filler; the length is proportionate to 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?

Given no output schema, the description carries the full burden of explaining return values and risk logic. It does this comprehensively: verdict values, per-leg detail, thin_legs[], max_clean_notional_usd, forced_directional_risk, and the real-world reason for the tool. It also covers both operational modes and edge cases like partial fills. This is a complete and self-contained specification.

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?

Even though schema coverage is 100%, the description enriches parameter understanding significantly. It explains that size_usd means 'max spend on buys, target proceeds on sells' in single-market mode, and 'settlement notional — shares per leg' in basket mode. It also clarifies that the side parameter defaults to 'auto' in basket mode based on partition sum. These nuances are not fully captured by 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 performs a 'realizable-vs-theoretical edge check' against live order book depth, and enumerates its two modes (single-market and basket). It explicitly positions itself as a pre-trade risk check relative to sibling tools polymarket_arbitrage and polymarket_edges, making its purpose unambiguous and well-differentiated.

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?

The description provides explicit when-to-use guidance: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains how to choose between market and event modes, and how side and size_usd behave differently in each mode, giving concrete direction on selection and invocation.

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

A3.9/5.0
Disambiguation2/5

Several tools are near-identical in purpose: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route the same style of question, and the company-research tools (entity_profile, compare_entities, recent_changes) and Polymarket tools (polymarket_edges, polymarket_arbitrage, bet_research) have overlapping triggers. The long descriptions help, but an agent could easily select the wrong one.

Naming Consistency3/5

All names are snake_case and mostly readable, but conventions are mixed: some are verb-led (ask_pipeworx, resolve_entity, scan_dependency), some are noun-led (entity_profile, pipeworx_feedback, polymarket_arbitrage), and some are adjective-noun phrases (recent_changes, recent_alerts). The polymarket_* and ask_pipeworx_* families are internally consistent, but the overall set has no unifying pattern.

Tool Count2/5

33 tools is high and the server bundles several unrelated domains: Pipeworx data research, prediction markets, PRIDE proteomics, memory, subscriptions, and AI-visibility checks. Each cluster is individually useful, but the aggregate surface feels over-stuffed rather than well-scoped for a single MCP server.

Completeness4/5

The main clusters are well covered: query/grounded/deep research, entity resolution/profile/compare/validate, memory CRUD, subscription lifecycle, and a rich Polymarket analytics toolkit. Minor gaps exist—PRIDE is limited to metadata search/get and there is no trade execution for prediction markets—but most workflows can be completed without dead ends.

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