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Whiskyhunter

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

A4.5/5.0
Behavior5/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false) already cover the safety profile, and the description adds substantial behavior beyond them: pairings are keyword/word-overlap matches that always carry pairing_unverified, spreads are gross because Kalshi's fee schedule is not modeled, legs with unknown metric_type/match_subtype are never paired, and compatibility codes can be non-empty even when matched_pairs>0. The null-means-unknown clarification for temporal_alignment preempts a likely misinterpretation.

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

Conciseness3/5

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

The description is front-loaded (purpose and modes in the first sentences) and nearly every sentence carries unique decision-relevant information. But it is a single unbroken ~400-word block with real redundancy: temporal_alignment_unknown is explained both in the compatibility-codes list and again in the temporal_alignment field note, and the keyword-overlap nature of pairing is stated twice. Paragraph breaks and trimming of the repeated semantics would improve scannability without losing content.

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 full responsibility for explaining the return shape — and it covers leg-by-leg prices, top_spreads_pp with per-entry flags[], compatibility_warning/codes[], skipped_unclassified, low_confidence_pairs[], temporal_alignment, fees_note, and the skipped_cross_type/subtype counters. For a dual-mode cross-venue tool with heavy interpretive caveats and three optional parameters, an agent has everything needed to invoke it and correctly interpret 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?

Schema coverage is 100%, setting a baseline of 3. The description adds cross-parameter meaning the schema lacks: explicit mode requires both kalshi_event_ticker and polymarket_event_slug together, each overrides its topic-mapped side, and both modes produce identical disclosure behavior. It also explains that the two modes are mutually exclusive alternatives rather than independent toggles. The 10 topic shortcuts are restated, which is redundant with the schema but harmless.

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?

States a specific verb and resource: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' The 2-25pp price-difference framing and participant-pool explanation tell an agent what kind of signal this produces and why. It clearly differentiates from the Polymarket-only siblings (polymarket_arbitrage, polymarket_edges) by anchoring on the Kalshi↔Polymarket same-question pairing.

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 TWO MODES are explained with explicit invocation conditions: topic shortcuts for pre-mapped macro events vs supplying both kalshi_event_ticker and polymarket_event_slug for custom pairings, with override semantics and the note that both run the identical matcher. The closing warning ('most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable') sets realistic expectations. However, no sibling tool is named and it never states when to choose this tool over polymarket_arbitrage or validate_claim, so full when/when-not guidance is missing.

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

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes (ask_pipeworx, ask_pipeworx_grounded, deep_research all perform research; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker are similar). Agents may struggle to pick the correct tool.

Naming Consistency2/5

Naming is inconsistent: some use snake_case (list_distilleries), others are descriptive (ask_pipeworx, deep_research), and some are branded (pipeworx_feedback). No clear pattern.

Tool Count3/5

33 tools is high but not unreasonable given the broad scope. However, the server name implies a whisky focus, making the count feel excessive for that domain.

Completeness2/5

For the whisky domain suggested by the name, only 3 tools are relevant. The rest are generic or unrelated (Polymarket, npm scanning), leaving significant gaps for whisky-specific tasks.