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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?

Even though annotations already mark the tool read-only, idempotent, and non-destructive, the description adds extensive behavioral context: compatibility codes and their meanings, unclassified legs never being paired, pairing_unverified always set, gross-vs-net fee disclosure, and temporal alignment null semantics. It also explains counters like skipped_cross_type/subtype.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long, but it earns its length: it is organized into modes, response, safety fields, code explanations, fee disclosure, and skipped-count semantics, and front-loads the core purpose before the caveats. No filler sentences are present and the structure makes the density navigable.

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 and no required parameters, the description must supply the full calling contract. It does: response shape, safety fields, possible codes, skipped-leg behavior, fee grossness, and caveats about pre-mapped topics. An agent has enough to decide when and how to call it and how to interpret the result.

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%, and the description goes further by explaining what each mode is for, that both modes run the identical overlap matcher, and what the explicit overrides do. It adds useful behavioral semantics beyond the field descriptions, though it doesn't address what happens when no parameters are supplied.

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?

Opens with a specific verb-resource statement: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' The two-mode explanation makes it clear what it computes and how, and the phrase 'same resolving question' distinguishes it from the polymarket-only siblings in the list.

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?

Provides clear mode-selection guidance (pre-mapped topics vs explicit ticker/slug), warns that pre-mapped topics often return compatibility warnings, and sets expectations that gross spread is not automatically a tradeable edge. It does not explicitly name sibling alternatives or say when not to use the tool, so it stops 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

B3.4/5.0
Disambiguation3/5

Many tools have distinct purposes, but there is notable overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, all serving data retrieval. Similarly, the Polymarket betting tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) share a domain, causing potential confusion for an agent.

Naming Consistency2/5

Tool names follow no consistent pattern: snake_case (ai_visibility_check), camelCase-like (bet_research, compare_entities), and noun-first (entity_profile, recent_changes) are mixed. The lack of a uniform verb_noun or other convention makes it harder to predict tool names.

Tool Count2/5

35 tools is excessive for a server named 'Osrm,' which suggests a focused routing engine. The actual tool set spans routing, data query, betting, entity resolution, and memory, indicating an overbroad scope that dilutes coherence.

Completeness3/5

The data query and betting tools are relatively comprehensive, but the routing side is minimal (missing isochrones, alternative routes). Gaps exist in general web search and coverage of other prediction markets. The server doesn't fully cover either the implied routing domain or the broader data/betting domain.