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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 read-only and non-destructive, but the description adds substantial behavioral context beyond them: it discloses that spreads are gross because Kalshi fees are not modeled, that compatibility_codes and pairing_unverified are always present when pairs are returned, that null temporal_alignment means unknown rather than aligned, and that unclassified legs are never paired. This is far beyond what the annotations alone imply.

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 front-loaded with purpose and mode selection, and uses labeled security and response sections. A few caveats are repeated (temporal_alignment_unknown appears twice, and 'pre-mapped ≠ tradeable' is stated twice), so it is not maximally tight, but the density is justified by the tool's compatibility nuances.

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 carries the full burden of explaining the response, and it delivers: raw leg prices, top_spreads_pp, compatibility_warning/codes, per-pair flags, skipped_unclassified/low_confidence_pairs, temporal_alignment semantics, skipped counters, and fees_note are all defined. An agent has enough information to invoke the tool and interpret even edge-case 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?

Schema coverage is 100%, so the baseline is 3; the description earns a 4 by clarifying the relationship between the three parameters — topic auto-fetches while the other two are for custom pairings, and 'BOTH modes run the identical token-overlap matcher.' It also repeats the shortcut list in a callable friendly form with examples in the schema, which is helpful but not a huge increment over 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 first sentence states a precise purpose: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' It distinguishes this from a generic arbitrage scan by emphasizing same-question comparison and bet-shape equivalence, and describes two concrete modes so an agent understands exactly what operation is being offered.

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 explicitly separates the topic shortcut mode from explicit ticker/slug pairing and notes both modes run the same matcher. It warns that pre-mapped topics often return compatibility warnings, but it does not explicitly compare against sibling tools such as polymarket_arbitrage, so the when-to-prefer-this-tool guidance is strong within the tool but not across siblings.

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
Disambiguation2/5

Several tools are deliberately near-identical variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) or have overlapping routing/query purposes (deep_research, validate_claim, discover_tools, suggest_questions). The Polymarket cluster also has five tools that all surface 'edges' or 'arbitrage' with only subtle differences. Only the three GeoNet tools and the memory trio are cleanly distinct.

Naming Consistency3/5

The dominant style is snake_case, and clusters like ask_pipeworx_* and polymarket_* are internally consistent. However, verb/noun patterns vary widely across the set: some tools begin with verbs (get_quake, scan_dependency, generate_llms_txt), some are noun phrases (entity_profile, volcano_alerts, recent_changes), and some are plain nouns (polymarket_arbitrage). Readable but not a single predictable convention.

Tool Count2/5

34 tools is well above the 'heavy' threshold, and the server is named 'Geonet Nz' while only 3 of its 34 tools relate to GeoNet. The overwhelming majority are Pipeworx/data/prediction-market tools, making the server's scope massively broader than its name implies. The count itself is not unreasonable for the actual feature sprawl, but it is inappropriate for the apparent purpose.

Completeness4/5

Taking the real scope as 'general authoritative data research + memory + subscriptions + a little GeoNet', the surface is quite complete: query entry points, grounded verification, deep research, entity resolution, comparisons, claim validation, monitoring subscriptions, memory persistence, and feedback are all present. The GeoNet-specific subset is also adequate (get one, list recent, volcano alerts). Minor gaps exist, like no general GeoNet station/well data or subscription editing, but nothing causes dead ends.