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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?

Annotations mark the tool read-only and idempotent, and the description adds substantial behavioral detail beyond that: fee modeling gaps, unverified pairings, exclusion of unknown legs, null temporal-alignment semantics, and per-pair flags. No contradiction with annotations.

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 well-organized with section labels and front-loaded purpose, but it is long and repeats several concepts, such as temporal_alignment_unknown being explained in multiple places. Every sentence adds some value, yet the overall length is heavier than necessary.

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 fully carries the burden of explaining the response structure, safety fields, compatibility codes, flags, skip counters, and fee disclosures. It gives an agent everything needed to interpret results correctly, including operational caveats like gross vs net spread.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters are already documented in the schema (100% coverage), so the baseline is 3. The description adds context about how explicit tickers override the topic-mapped sides, but does not materially deepen individual parameter meaning beyond 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?

States a specific verb and resource: cross-venue spread between Kalshi and Polymarket for the same resolving question. The two modes (topic shortcuts vs explicit tickers) further define the tool's scope. Although it doesn't explicitly name sibling tools, the venue-specific purpose is unambiguous.

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?

Explains both invocation modes with concrete examples and override semantics, plus a caution that pre-mapped topics often return compatibility warnings. Does not explicitly contrast against sibling tools like polymarket_arbitrage, but provides clear context for when and how to use it.

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

A3.8/5.0
Disambiguation2/5

The tool set mixes several distinct domains (satellite orbital data, Pipeworx data routing, prediction-market analysis, memory management, subscriptions), but within the Pipeworx umbrella there is heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language questions to the same underlying 5,756 tools. An agent could easily misselect between them, especially since ask_pipeworx and ask_pipeworx_beta are described as currently identical.

Naming Consistency3/5

Many tools follow a clear verb_noun pattern (list_subscriptions, create... none, but compare_entities, resolve_entity, generate_llms_txt, scan_dependency, subscribe/unsubscribe, remember/recall/forget), yet the naming is inconsistent across the set: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, get_satellite, get_group, recent_alerts, recent_changes, entity_profile, and deep_research do not share a uniform convention. CamelCase appears in polymarket_arbitrage, polymarket_edges, etc. while most others are snake_case, and the satellite tools (get_satellite, get_group, search_by_name) form a distinct sub-pattern that clashes with the Pipeworx meta-tools.

Tool Count2/5

34 tools is on the heavy side, and the effective surface is bloated: there are three variants of ask_pipeworx, four polymarket_* tools, three satellite-specific tools that are unrelated to the server's apparent core purpose, and several meta/utility tools (remember, recall, forget, pipeworx_feedback, pipeworx_trending, suggest_questions) that could be consolidated or are only tangentially related. The count itself is not extreme, but the scope is muddled: the server claims the name Celestrak (satellite tracking) while the overwhelming majority of tools are for Pipeworx data access and prediction markets, making the tool count feel inappropriate for either purpose.

Completeness3/5

For the Pipeworx data-access domain, the tool set is quite thorough: natural-language routing, grounded answers, deep research, entity profiling, entity comparison, claim verification, semantic search, and tool discovery are all present. However, there are notable gaps: the subscription lifecycle lacks an update/resume mechanism, and the satellite domain (the server's namesake) is severely incomplete — only three lookup tools with no live tracking, no group listing beyond a handful of groups, and no clear lifecycle CRUD. The memory tools (remember/recall/forget) are minimal but complete for their narrow scope.