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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. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Even though annotations already mark this as read-only and idempotent, the description adds extensive behavioral context: gross spread not net of Kalshi fees, compatibility_codes that can be non-empty with returned pairs, null semantics for temporal_alignment, skipped-leg counters, and explicit warnings that matching is keyword-based rather than verified by a shared resolution source. This materially exceeds what the annotations convey.

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 dense and mostly well-organized with labeled sections like RESPONSE and SAFETY FIELDS, but it is long and somewhat repetitive, notably re-explaining temporal_alignment_unknown in two places. It carries a high information load, yet could be tightened without losing meaning.

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?

Despite having no output schema, the description thoroughly covers return values, safety fields, flags, skipped comparisons, fee treatment, and null semantics. It gives an agent everything needed to interpret the result correctly, including the critical warning that non-empty compatibility fields do not imply a valid tradeable spread.

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?

The schema already has full coverage and descriptive parameter text, so the baseline is 3. The description adds value by explaining that both modes run the same token-overlap matcher, that explicit ticker/slugs override the topic mapping, and that the pre-mapped topic list is not a guarantee of tradeability. It does not go beyond that enough to warrant a 5.

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 description clearly states a specific function: compute the cross-venue spread between Kalshi and Polymarket for the same resolving question, and distinguishes itself from single-venue tools. However, it does not explicitly differentiate itself from sibling tools like polymarket_arbitrage or polymarket_edges, so the distinction is implicit rather than direct.

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 gives strong within-tool usage guidance: when to use the pre-mapped `topic` shortcuts versus explicit `kalshi_event_ticker` and `polymarket_event_slug` pairings, and warns that pre-mapped topics often are not tradeable. It does not explicitly tell the agent when to prefer this tool over its siblings, so it falls 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

A3.9/5.0
Disambiguation3/5

Tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research serve similar querying purposes, and there is overlap among prediction market tools (e.g., polymarket_arbitrage, polymarket_edges). However, descriptions help differentiate them, so agents can usually select the correct one.

Naming Consistency3/5

Most tools use snake_case with verbs (ask_, resolve_, validate_), but there are noun-style exceptions (entity_profile, recent_changes, pipeworx_trending) and mixed naming among Polymarket tools. The pattern is readable but not fully consistent.

Tool Count2/5

With 32 tools, the server feels bloated, especially given the name 'Cdc' implies a focus on CDC data, yet many tools cover unrelated domains like prediction markets and company profiles. Several tools could be consolidated or removed to align with a narrower scope.

Completeness3/5

The CDC domain is thinly covered with only search and get for datasets, lacking upload or advanced filtering. Company financials are limited to basic fundamentals from 10-Ks. Prediction markets are well-covered with arbitrage, edges, and fill risk. The server has notable gaps in its core domain.