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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

A4.3/5.0
Behavior5/5

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

The description goes far beyond the readOnly/openWorld/idempotent annotations by disclosing matching limitations (keyword overlap, pairing_unverified), temporal alignment caveats, unclassified-leg exclusion, skipped-cross counters, and the fact that spreads are gross because Kalshi fees are not modeled. It also clarifies that null temporal_alignment means 'could not be computed,' not 'aligned.' 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, but it is well-structured into modes, response contents, safety fields, codes, skipped counters, and fee caveats, and the core purpose is front-loaded. Because there is no output schema, the description must carry the operational detail; still, a few sections could be tightened without loss.

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?

With no output schema, the description documents the response shape, safety fields, compatibility codes, per-entry flags, skipped categories, temporal alignment semantics, and the standing fee disclosure. An agent has enough information to invoke the tool correctly, interpret warnings, and understand why a spread may not be a real tradable edge.

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%, so the schema already documents each parameter. The description adds meaning by explaining the topic enum as 10 pre-mapped shortcuts, stating that explicit ticker/slug override the mapped side, and noting that both modes run the identical matcher. This is useful enrichment beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence states the exact function: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' This is a precise, specific resource-and-operation description. It does not, however, explicitly distinguish itself from sibling tools like polymarket_arbitrage or polymarket_edges, so it stops short of the full 5.

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?

The description clearly explains the two invocation modes — topic shortcuts versus explicit kalshi_event_ticker + polymarket_event_slug — and warns that pre-mapped topics frequently return compatibility warnings, so they are not automatically tradeable. It does not explicitly name alternative sibling tools or state when to prefer them.

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

A3.6/5.0
Disambiguation2/5

Several tools occupy nearly identical roles: ask_pipeworx and ask_pipeworx_beta are described as currently identical, ask_pipeworx_grounded and deep_research overlap with the router, and eia_series overlaps with the specialized eia_electricity/eia_ethanol/eia_natural_gas/eia_petroleum tools. The Polymarket opportunity scanners and the two AI-visibility checkers also blur together, making confident tool selection difficult despite detailed descriptions.

Naming Consistency3/5

Most tools follow a snake_case verb-first pattern (remember, recall, forget, resolve_entity, validate_claim), but there are notable deviations: eia_electricity and eia_ethanol are noun-first category names, recent_alerts and recent_changes are adjective-noun, and pipeworx_trending and polymarket_edges are not verb-driven. The eia_ and polymarket_ prefixes add some predictability, so the naming is readable but inconsistent.

Tool Count2/5

At 36 tools, this is well past the heavy threshold and feels like a kitchen-sink aggregation of several separate products rather than one focused server. Many tools could be consolidated: the five eia_* lookups, the multiple ask_pipeworx variants, and the several Polymarket scanners all serve close purposes. A 36-tool surface is too much for an agent to navigate efficiently.

Completeness4/5

Within the major subdomains the set is quite complete: entity research has profile/compare/changes/resolve, memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and Polymarket analysis has edge discovery, fill-risk, venue-spread, and persistence tracking. Minor gaps exist—no subscription update flow, no dedicated EIA coal/nuclear/renewables series beyond the generic eia_series fallback—but agents can work around them.