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Predictit

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

A4.2/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds extensive behavioral context beyond that: the compatibility_warning/compatibility_codes system, temporal null semantics ('null means it could not be computed, not that the two sides align'), the fee disclosure that spreads are gross, and the skipped_cross_type/skipped_cross_subtype counters. This is rich, non-obvious behavior fully disclosed.

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?

Every sentence carries substantive information, but the description is a dense, continuous prose block mixing mode instructions, response fields, safety codes, temporal semantics, fee caveats, and skipped-count details. It would be more usable with headings, bullets, or a clearer separation of 'how to call' vs 'what to interpret.' It is thorough but not concise in structure.

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?

Given no output schema, the description is unusually complete: it documents response fields (leg prices, top_spreads_pp), safety fields and their codes, per-entry flags, skipped/unclassified handling, temporal alignment semantics, fee limitations, and behavior in both modes. An agent has enough to invoke the tool and interpret results correctly without additional external knowledge.

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 each parameter is already documented; the baseline is 3. The description adds real value by explaining that topic mode auto-fetches matching events, that explicit ticker/slug overrides operate independently, and that BOTH modes run the identical token-overlap matcher. This goes beyond the schema's field-level descriptions and clarifies how the three parameters interact.

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 opens with a clear, specific statement: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' It names the resource (Kalshi/Polymarket), the output (spread), and the two operating modes. However, it does not explicitly contrast itself with sibling tools like polymarket_arbitrage or polymarket_edges, so an agent must infer the differentiating factor.

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 substantial usage context, including the two modes, how to invoke them, and a clear caution: 'pre-mapped ≠ tradeable' and 'Real cross-venue spreads are rarer than the macro-shortcut list suggests.' It also explains when the spread is a real signal ('when the bet shapes are equivalent') versus when it is not. It stops short of naming alternative tools to use instead, so the 'when-not-to-use' guidance is only implicit.

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

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes, but pairs like ask_pipeworx/ask_pipeworx_grounded and bet_research/polymarket_edges could cause confusion without careful reading. Overall, descriptions are clear enough to differentiate.

Naming Consistency3/5

Names are snake_case and mostly follow verb_noun pattern, but several are noun_noun (entity_profile, pipeworx_feedback, polymarket_arbitrage) creating inconsistency. Still readable due to descriptive terms.

Tool Count4/5

33 tools is slightly high but justified given the broad scope (data retrieval, prediction markets, memory, subscriptions). Each tool serves a specific role, so the count feels appropriate for the platform's capabilities.

Completeness4/5

The tool set covers data retrieval, prediction market analysis, memory management, and subscriptions well. Minor gaps exist (e.g., no direct betting tool), but core workflows are supported comprehensively.