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Stripe_connect

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

A4.6/5.0
Behavior5/5

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

Annotations indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable context: it explains that the tool walks the order book ladder, returns specific metrics like slippage and fill details, and warns about thin books and unhedged positions, all beyond what annotations provide.

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

Conciseness3/5

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

The description is well-structured with clear sections for single-market and basket modes, but it is verbose with multiple paragraphs and repetitive detail. While informative, it could be more concise to allow quicker parsing by an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of an output schema, the description thoroughly explains return values for both modes, including specific fields like vwap_fill_price and capture_ratio. It also covers usage context and risks. This makes the tool largely self-contained, though exact field names in the output are not listed.

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% with parameter descriptions. The description adds significant meaning by explaining default behaviors (e.g., side auto-detection in basket mode) and different interpretations of size_usd for single-market vs basket. This goes beyond the schema, justifying a score above the baseline of 3.

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 it performs a 'realizable-vs-theoretical edge check against live CLOB order-book depth' and distinguishes two distinct modes (single-market and basket). This specificity differentiates it from sibling tools like polymarket_arbitrage and polymarket_edges.

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 explicitly instructs to 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. It also warns against using it for partial basket fills, providing clear when-to-use and when-not-to-use guidance.

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

B3.3/5.0
Disambiguation2/5

The set has several near-duplicate entry points: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, while ask_pipeworx_grounded/deep_research and bet_research/polymarket_edges overlap heavily. Verbose descriptions help in isolation, but an agent must choose between many similar-looking research and prediction-market tools before it can act.

Naming Consistency2/5

Naming mixes bare verbs (remember, forget, subscribe), prefixed families (pipeworx_*, polymarket_*, stripe_*), and descriptive noun-style names (entity_profile, validate_claim) with no single verb_noun pattern. Each cluster is internally consistent, but the overall set is unpredictable.

Tool Count2/5

37 tools is excessive for a server named Stripe_connect, especially since only 6 tools are actually Stripe-related and the rest are a sprawling Pipeworx data-research and prediction-market stack. The count would be heavy even for the broad research domain, and it is a serious scope mismatch for the stated name.

Completeness1/5

For the Stripe domain implied by the server name, the surface is severely incomplete: it is read-only (get/list) with no way to create customers, take payments, issue refunds, update invoices, or manage subscription lifecycles. The non-Stripe research tools are broad, but that does not fill the payment workflow gap.

Resources