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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

A4.1/5.0
Behavior5/5

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

With readOnlyHint and idempotentHint already supplied by annotations, the description goes well beyond them by disclosing non-obvious behavior: compatibility codes, gross-fee modeling limitations, never pairing unknown legs, skipped comparison counters, and the exact meaning of null temporal alignment. No annotation is contradicted.

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 deliberately organized with labeled sections for modes, response, safety fields, and caveats, and it front-loads the core purpose. Some temporal-alignment detail is repeated, but most sentences earn their place given the tool's complexity and the absence of an 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?

Because there is no output schema, the description is the sole source for response semantics, and it thoroughly covers top_spreads_pp, compatibility fields, per-leg flags, skipped counters, fee disclosures, and temporal alignment null semantics. Minor gaps like no-parameter behavior are not enough to undermine its completeness.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all three parameters. The description adds useful mode-level context about how topic and explicit parameters interact, but it does not materially deepen the per-parameter semantics beyond what the schema provides.

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 unambiguously identifies the tool's function: a cross-venue spread between Kalshi and Polymarket for the same resolving question, with two distinct modes. It is clearly differentiated from same-venue tools, though it does not explicitly name or distinguish itself from the similar polymarket_arbitrage sibling.

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 when to use topic shortcuts versus explicit kalshi_event_ticker + polymarket_event_slug pairings, and warns that most pre-mapped topics are not currently tradeable. It provides clear context and caveats, but does not explicitly contrast this tool against sibling alternatives like polymarket_arbitrage.

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

A3.8/5.0
Disambiguation3/5

Most tools have distinct purposes, but the ask_pipeworx trio (stable, beta, grounded) are near-identical variants, and the five polymarket_* tools plus bet_research heavily overlap in the edge-finding space. Detailed descriptions help, but an agent could easily misselect among these clusters.

Naming Consistency3/5

Names are all snake_case and readable, but conventions vary: ask_pipeworx_* uses a prefix pattern, polymarket_* is consistent, yet others mix verbs (scan_competitor_ai_presence, generate_llms_txt) with nouns (entity_profile, resolve_entity). No single verb_noun pattern governs the set.

Tool Count2/5

34 tools is well above the 25-tool threshold and feels like multiple servers merged into one: structured data routing, prediction markets, OSM, memory, subscriptions, and AI-visibility checks. The breadth is impressive but the count is heavy for a single tool surface.

Completeness4/5

The surface is notably complete for its blended domain: memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe, data access has multiple router modes plus deep research and claim validation, and prediction markets have research, edge, arbitrage, fill-risk, and cross-venue tools. Minor gaps exist (no subscription update, no explicit reverse-geocoding tool), but core workflows are covered.