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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 readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description adds substantial non-annotated behavior: pairing_unverified is set whenever pairs are returned, null temporal_alignment means 'could not compute' rather than aligned, unknown legs are never paired, and fees are gross rather than net tradeable edge. No contradiction exists between the annotations and the description.

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 and dense, but it is well-structured with clear thematic sections: purpose, modes, response, safety fields, compatibility codes, skipped counts, and fee disclosure. Every sentence adds meaningful safety or usage information, and the core purpose is front-loaded. It is not pithy, but the tool's complexity and absence of an output schema make the thoroughness appropriate.

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 effectively documents the response shape, including leg-by-leg prices, matched spread entries, top_spreads_pp, compatibility codes, temporal alignment status, skipped-leg counters, and the standing fee caveat. An agent has enough information to select the tool, invoke it correctly in either mode, and interpret safety-critical results.

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 input schema already documents all three parameters at 100% coverage, so the baseline is 3. The description adds useful semantic context beyond the schema, such as that both modes run the identical token-overlap matcher and that explicit ticker/slug fields override the topic-mapped side. This justifies slightly above the baseline.

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 precise object and scope: a cross-venue spread between Kalshi and Polymarket for the same resolving question. It then names the two modes and the response contents, clearly differentiating this from polymorphic polymarket-only sibling tools. This is more than a tautology or vague paraphrase of the title.

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 gives concrete mode-selection guidance: topic shortcuts for pre-mapped macros versus explicit kalshi_event_ticker and polymarket_event_slug for custom pairings. It also warns that most pre-mapped topics currently return compatibility_warning and that pre-mapped is not tradeable. It does not explicitly name sibling alternatives or state when not to use the tool, but the context is clear enough.

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
Disambiguation3/5

Most tools have detailed, carve-out descriptions, but ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same routing core, with the beta version currently identical to the stable one. The Polymarket and company-research clusters are better differentiated, but the number of overlapping research/query entry points still creates real selection risk.

Naming Consistency3/5

The set is consistently snake_case and has coherent prefixes like ask_pipeworx_ and polymarket_, but it mixes verb_noun names (resolve_entity, scan_dependency, discover_tools) with noun-phrase names (entity_profile, bet_research, recent_changes) and one-word verbs (remember, recall, forget). The naming is readable but does not follow one predictable pattern.

Tool Count2/5

With 32 tools, the server exceeds the 25+ threshold for too many tools and feels like a broad platform dump rather than a focused toolkit. Several utility, memory, and meta-discovery tools could reasonably live in separate servers, and the Insee name makes the breadth especially unfocused.

Completeness4/5

For the broad data-research platform it actually exposes, the coverage is strong: general lookup, grounded verification, deep research, entity resolution, company profiles, comparisons, change feeds, subscriptions, and memory all have working lifecycles. The main gap is that some unrelated utilities like scan_dependency and generate_llms_txt feel tacked on rather than part of a missing core workflow.