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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

A4.3/5.0
Behavior5/5

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

The description goes well beyond the read-only/idempotent annotations, detailing that unknown legs are never paired, temporal_alignment_unknown does not mean aligned, spreads are gross and do not model Kalshi fees, and compatibility codes can be non-empty even when pairs are returned. This is strong, candid behavioral disclosure.

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 well-organized with uppercase labels, compact code lists, and front-loaded core meaning. Some details are slightly redundant, especially around temporal_alignment_unknown and the safety fields, but the complexity of the tool justifies most of the length.

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 present, the description carries the full burden of explaining the response and it does so thoroughly: response shape, top_spreads_pp flags, skipped_unclassified, temporal_alignment fields, fees_note, skipped counters, and compatibility codes. An agent has enough context 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 covers all three parameters, so the baseline is 3. The description adds meaningful mode semantics: topic auto-fetches matching events, custom ticker/slug pairings override the mapped sides, and both modes run the identical matcher with the same disclosures. That is valuable beyond the schema text.

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 description clearly identifies the resource: the cross-venue spread between Kalshi and Polymarket for the same resolving question, and it explains the two modes of operation. However, it does not explicitly differentiate itself from sibling tools like polymarket_arbitrage or polymarket_edges, so it stops short of the distinguishing criterion for a 5.

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 explicit mode guidance: use topic for pre-mapped shortcuts, or supply kalshi_event_ticker + polymarket_event_slug for custom pairings. It also warns that pre-mapped topics are not automatically tradeable. It does not explicitly name alternative tools for when this tool should not be used, so it earns a 4 rather than 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

A3.7/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical, while ask_pipeworx_grounded, deep_research, validate_claim, and entity_profile all perform data lookups with only subtle differences. discover_tools and suggest_questions also serve similar onboarding/exploration roles.

Naming Consistency4/5

Tool names are uniformly snake_case and generally follow a verb_noun or noun_phrase pattern (e.g., ask_pipeworx, query_layer, entity_profile, remember). There is a slight mix between verb-first and noun-first names but no chaotic conventions like camelCase or inconsistent verb tense.

Tool Count2/5

At 34 tools, the count is well above the typical 15-25 range for a coherent server. More critically, the server is named 'Arcgis Lakecountyil' but only 3 tools (search_datasets, layer_info, query_layer) actually relate to ArcGIS; the remaining 31 tools are a broad Pipeworx data platform, creating a severe scope mismatch that makes the count feel excessive and unfocused.

Completeness2/5

For the ArcGIS domain implied by the server name, the surface is barely complete: it offers search, schema inspection, and querying, but no create, update, delete, or management capabilities. Conversely, the Pipeworx side is relatively rich, but that doesn't match the server's stated purpose, leaving the overall set incomplete for its apparent intended use.