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Stripe_connect

by io.github.pipeworx-io

Polymarket–Kalshi Spread

polymarket_kalshi_spread
Read-onlyIdempotent

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) topic — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit kalshi_event_ticker + polymarket_event_slug for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoPre-mapped: fed | btc | cpi | gdp | sp500 | recession | next_pope | next_uk_pm | next_israel_pm | 2028_president
kalshi_event_tickerNoExplicit Kalshi event ticker, e.g. "KXFED-26OCT". Overrides the topic-mapped Kalshi side.
polymarket_event_slugNoExplicit Polymarket event slug, e.g. "fed-decision-in-june-825". Overrides the topic-mapped Polymarket side.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "topic": "fed"
+  },
+  {
+    "topic": "btc"
+  }
+]
  2. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already mark the call read-only, idempotent, and non-destructive, and the description goes far beyond them: it discloses the token-overlap matching heuristic, the meaning of null temporal alignment, that warnings can be non-empty even with returned pairs, fee handling (gross not net), and skipped-comparison counters. 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?

The description is long and dense, but the complexity justifies most of the length: no output schema exists, so safety codes, flags, and fee disclosures must be inline. It is front-loaded with purpose and modes before caveats; still, a few reminders (e.g., 'NOT the same as confirmed-aligned') are repeated or could be tightened.

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?

For a read-only cross-venue tool with no output schema, the description thoroughly covers return fields, safety codes, skipped legs, fee treatment, and null semantics. The main gap is that with zero required parameters it never states what happens when neither a topic nor explicit pairings are supplied, or whether a custom pairing requires both ticker and slug.

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%, and the description still adds value by defining the two modes, listing the exact pre-mapped topics, and explaining that explicit ticker/slug parameters override the topic-mapped side and that both modes share the same matcher. That is meaningful beyond the schema, though some details simply restate the schema's examples.

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 opens with a specific verb and resource — 'Cross-venue spread between Kalshi and Polymarket for the same resolving question' — and immediately scopes the tool to same-question pairs, distinguishing it from the numerous polymarket-only siblings and arbitrage/fill-risk tools. The two-mode breakdown (topic shortcuts vs explicit ticker/slug) further clarifies exactly what resource is operated on.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear context for when the spread is meaningful ('when the bet shapes are equivalent that delta is a real signal') and when it is not, and it explains both invocation modes. It does not explicitly name sibling alternatives or state 'use X instead when...', so it stops short of a 5.

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.

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