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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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the bar is lower, and the description adds substantial behavioral context anyway. It discloses that Kalshi fees are not modeled, that spreads are gross rather than net tradeable edge, that unclassified legs are never paired, and that temporal_alignment null means 'could not be computed' rather than aligned. No contradiction with annotations exists.

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 dense and front-loaded: purpose, modes, response shape, safety fields, and caveats appear in logical order. Every sentence contributes information not available from the schema or annotations, though some repetition of compatibility codes could be tightened. It is appropriately detailed for a tool with no output schema.

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 bears the full burden of explaining return behavior and interpretation, and it does so thoroughly. It covers top_spreads_pp, per-entry flags, safety fields, skipped_unclassified, low_confidence_pairs, temporal_alignment semantics, fee disclosure, and skipped-cross counters. An agent has enough to invoke either mode and correctly interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the three optional parameters, so the baseline is 3, but the description adds significant meaning: it defines the two modes, explains how explicit parameters override mapped sides, and provides concrete examples like KXFED-26OCT and fed-decision-in-june-825. It also clarifies that both modes run the same token-overlap matcher.

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 states a specific resource and computation: the cross-venue spread between Kalshi and Polymarket for the same resolving question. It clearly distinguishes this from sibling Polymarket tools by describing the two-venue comparison and the topic/explicit pair modes. The purpose is immediately understandable and actionable.

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 explains exactly when to use the built-in topic shortcuts versus explicit kalshi_event_ticker and polymarket_event_slug pairings, and warns that most pre-mapped topics return compatibility_warning today. It also tells agents to read safety fields even when matched_pairs>0. It does not explicitly name sibling alternatives like polymarket_arbitrage, so it stops short of full alternative-routing 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

A4/5.0
Disambiguation4/5

Most tools have distinct purposes with clear descriptions, but the multiple ask_pipeworx variants and several Polymarket tools could cause initial confusion. An agent reading carefully can differentiate them, but the similarity in themes requires attention.

Naming Consistency3/5

Names use a mix of conventions: verb_noun (ask_pipeworx, compare_entities), noun_noun (entity_profile, dataset_columns), and single verbs (remember, forget). While some subgroups have internal consistency (e.g., polymarket_*), there is no overall predictable pattern.

Tool Count2/5

With 34 tools, the count exceeds the 'too many' threshold of 25. While the server is comprehensive, the large number of highly specific tools (especially for prediction markets) feels overwhelming and could confuse agents.

Completeness4/5

The tool set covers a wide range of capabilities: data querying, entity resolution, company analysis, prediction markets, memory, subscriptions, and validation. Minor gaps exist (e.g., no data writing tools), but for the read-heavy analytical purpose, it is nearly complete.