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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.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds extraordinary non-obvious behavior on top: temporal_alignment null 'means it could not be computed... not that the two sides align,' unknown metric_type/match_subtype legs are 'NEVER paired,' compatibility codes 'can be non-empty... even when matched_pairs>0,' pairing_unverified applies in EITHER mode, and every spread_pp is gross, not net tradeable edge. 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?

Long (~450 words) but every sentence earns its place — dense operational detail with no filler. Sections are logically ordered: purpose, modes, response, safety fields, code semantics, null semantics, fees, caveat. Not a 5 only because the code-by-code explanations are extensive and some could have been compressed, though the complexity arguably justifies the length.

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?

No output schema exists, so the description correctly carries the burden of explaining return values: response shape, the Kalshi − Polymarket sign convention in top_spreads_pp, compatibility_warning/codes, per-entry flags[], skipped_cross_type/subtype counters, temporal_alignment shape and null semantics, and the standing fee disclosure. For a two-venue, two-mode tool with this many caveats, nothing an agent needs to call it correctly is missing.

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 baseline is 3, but the description adds relational semantics beyond the schema: explicit ticker/slug 'Override[s] the topic-mapped' side, and 'BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both.' This clarifies how the three parameters interact, which the schema alone does not convey.

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 opening sentence states a specific verb and resource: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' It distinguishes itself from polymarket-internal siblings (polymarket_arbitrage, polymarket_edges) by venue scope, and adds interpretive context ('when the bet shapes are equivalent that delta is a real signal').

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?

Explicit TWO MODES with selection criteria: topic shortcuts for 10 pre-mapped macros vs explicit kalshi_event_ticker + polymarket_event_slug for custom pairings, and a clear caution that 'pre-mapped ≠ tradeable' / 'most pre-mapped topics return compatibility_warning today.' However, it never names sibling alternatives (e.g., no explicit 'use polymarket_arbitrage for within-venue comparisons'), so the when-not-to-use guidance is implied rather than stated.

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

The set contains several heavily overlapping clusters: three ask_pipeworx variants (with ask_pipeworx_beta explicitly identical to ask_pipeworx right now) and six polymarket-related tools that all orbit edge detection, arbitrage, and fill risk. An agent choosing among bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_kalshi_spread would have a hard time picking the right one.

Naming Consistency3/5

Most tools use readable snake_case, so the naming is not chaotic. However, the pattern is mixed: some are verb_noun (compare_entities, resolve_entity), some are brand-style (ask_pipeworx, ask_pipeworx_beta), and some are noun-only phrases (events, polymarket_arbitrage, pipeworx_trending). It is consistent in casing but not in structural convention.

Tool Count2/5

32 tools is well beyond the usual well-scoped range, and the count is inflated by multiple near-duplicate clusters for querying, prediction markets, and memory/subscription utilities. For a server named Madrid Events, this is especially disproportionate since only one tool actually relates to Madrid events.

Completeness2/5

Relative to the Madrid Events name, the domain coverage is almost entirely missing: only events addresses the stated purpose, and it is read-only with no detail view, booking, or management operations. If interpreted as the broader Pipeworx platform, coverage is richer, but the server's stated identity makes the gap severe.