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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?

Despite the readOnly/idempotent annotations already signaling safety, the description adds extensive behavioral context: the token-overlap matching approach, non-equivalent bet shape detection, compatibility codes, `temporal_alignment_unknown` semantics, gross-vs-net fee disclosure, skipped comparison counters, and the explicit warning that returned pairs may still be unverified. This far exceeds what annotations alone convey and does not contradict them.

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 and dense, but it is structured into purpose, modes, response, safety fields, and skipped-comparison semantics, and nearly every sentence carries operational value for a complex comparison tool. It is not as tight as it could be—some warnings repeat across the safety-fields list and the codes explanation—but the length is largely justified by the tool's complexity.

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 response semantics, and it does so thoroughly: it names `top_spreads_pp`, per-entry flags, `skipped_unclassified`, `low_confidence_pairs`, `temporal_alignment`, `fees_note`, and the skipped-cross counters. An agent has enough context to invoke the tool, interpret warnings, and avoid treating unmatched or unknown legs as tradeable signals.

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, but the description adds meaningful semantics beyond the schema by explaining the two invocation modes, that both modes run the identical token-overlap matcher, and how explicit ticker/slug parameters override the topic-mapped side. This helps an agent choose and combine the three parameters correctly rather than just knowing their types.

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 tool as computing a cross-venue spread between Kalshi and Polymarket for the same resolving question, which is specific enough to distinguish it from the sibling polymarket-edge tools. It lacks an explicit verb like 'returns' or 'computes' and does not directly compare itself to any sibling, so it stops short of 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 clear mode-based guidance: use `topic` for pre-mapped macro shortcuts and use explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings, noting both run the same matcher. It also warns that most pre-mapped topics currently return compatibility warnings, managing expectations. However, it never explicitly contrasts the tool with sibling tools like polymarket_arbitrage or polymarket_edges, so usage guidance is context-rich but not full alternative-routing guidance.

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

Several tools have significantly overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all perform data retrieval, with beta currently identical to stable. The polymarket_* family and bet_research also blur boundaries, and discover_tools vs suggest_questions both handle discovery. Despite detailed descriptions, agents are likely to misselect among these overlapping options.

Naming Consistency3/5

All tools use snake_case, but conventions are mixed: some start with verbs (get_launch, search_launches, ask_pipeworx), others are noun phrases (entity_profile, pipeworx_trending), and there are versioned suffixes (ask_pipeworx_beta). While each domain group has internal consistency, the overall set lacks a unified pattern.

Tool Count2/5

35 tools is excessive for a server named 'launches'—only 4 tools (get_launch, get_past_launches, get_upcoming_launches, search_launches) actually relate to space launches. The remaining 31 tools cover unrelated domains like prediction markets, company profiles, and memory, making the count inappropriate and diluting the server's focus.

Completeness2/5

For the claimed launch domain, the set provides only basic list/detail/search operations and lacks useful launch features like filtering by agency, date range, or launch site. More critically, the inclusion of 31 unrelated tools creates a fragmented surface with obvious dead ends—an agent expecting a launch-focused server would find most tools irrelevant.