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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 mark the tool readOnly, openWorld, idempotent, and non-destructive, so the bar for additional disclosure is lower. The description goes far beyond annotations by explaining safety fields, compatibility codes, fee structure, gross-vs-net spread semantics, pairing-unverified status, skipped comparison counters, and the null-means-unknown temporal alignment behavior. This is exemplary behavioral transparency.

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 densely structured and front-loaded with purpose, then modes, then response semantics, then safety fields. Nearly every sentence adds necessary operational nuance for a tool that has no output schema and complex return flags. It earns a 4 rather than 5 because some caveats (e.g., temporal alignment semantics) are restated at multiple points, creating minor redundancy.

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?

Given the tool's complexity and the absence of an output schema, the description is remarkably complete. It covers return values, spread sign convention, compatibility codes, per-entry flags, skipped-leg counters, fee caveats, unclassified leg handling, and null semantics for temporal alignment. An agent has enough information to invoke the tool and interpret its results correctly.

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 documents all three parameters with 100% coverage, including enum values and example tickers, so the baseline is 3. The description adds meaningful context on top: it explains that topic mode auto-fetches matched events, that explicit parameters override the mapped side, and that both modes run the same matcher. It does not simply restate the schema.

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 clear verb and resource: it computes the cross-venue spread between Kalshi and Polymarket for the same resolving question. It also names the two distinct invocation modes (topic shortcuts vs explicit ticker/slug pairings), making the tool's purpose and scope unmistakable. It distinguishes itself from sibling tools like polymarket_arbitrage by focusing specifically on the cross-venue Kalshi–Polymarket comparison.

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 how to use both modes and when each is appropriate, and explicitly warns that pre-mapped topics are not automatically tradeable. It does not explicitly name alternatives or state when another tool should be used instead, but it gives strong operational guidance within the tool's intended use case.

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
Disambiguation4/5

Most tools have distinctly described purposes, but there is some overlap among query tools like ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim, which could cause confusion for an agent.

Naming Consistency3/5

Tool names are consistently snake_case but vary in pattern: some are verb_noun (ask_pipeworx, compare_entities), while others are noun_noun (entity_profile, polymarket_arbitrage) or longer phrases (scan_competitor_ai_presence), making the naming system inconsistent.

Tool Count2/5

With 33 tools, the server feels over-scoped. Many tools are niche (e.g., polymarket-specific ones) and the high number exceeds the typical range for a focused server, leading to potential overwhelm.

Completeness3/5

The server covers a broad range of query and monitoring tasks for its domains, but lacks write operations (except memory tools). There are notable gaps like no tool for creating or editing ScienceBase items, which seems incomplete given the server's name.