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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 declare readOnly/idempotent/openWorld, and the description adds substantial behavioral disclosure: pairing is keyword-based and unverified, compatibility_codes can be non-empty even on returned pairs, temporal_alignment null means unknown rather than aligned, and spreads are gross of Kalshi fees. This goes far beyond what annotations provide.

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 well-structured with labeled sections (MODES, RESPONSE, SAFETY FIELDS, fees, counters) and a clear front-loaded purpose. There is some redundancy—temporal_alignment_unknown and pairing_unverified are explained multiple times—which prevents a perfect score, but each major section earns its place given 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?

There is no output schema, so the description carries the full burden of explaining return values, and it does so thoroughly: leg prices, top_spreads_pp, compatibility_warning/codes, flags[], skipped_unclassified, temporal_alignment, skipped counters, and fees_note. It also warns about empty/unverified results and what each warning flag means, leaving no essential call-time ambiguity.

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 adds the full topic enum list, explains that explicit ticker/slug values override the topic-mapped side, and stresses that both modes run the identical matching logic. This is meaningful semantic context beyond the schema's simple field descriptions.

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 opening sentence states exactly what the tool computes: a cross-venue spread between Kalshi and Polymarket for the same resolving question. It names both venues, the object of comparison, and the notion of resolution alignment, distinguishing it from Polymarket-only sibling tools. This is a specific verb+resource statement, not a tautology.

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 defines two explicit invocation modes (topic vs explicit kalshi_event_ticker + polymarket_event_slug) and explains when each is appropriate. It gives clear usage context, including that pre-mapped topics are not automatically tradeable, but it does not explicitly name sibling alternatives or exclusion criteria.

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

B3.4/5.0
Disambiguation3/5

Tools are generally distinguishable by name and description, but there are several similar query/verification tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) and multiple meta-tools (discover_tools, suggest_questions), causing some ambiguity for agents.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use verb_noun (search_projects, validate_claim), others are noun_preposition_noun (projects_by_country), single verbs (remember, forget), or compound phrases (generate_llms_txt). No clear pattern.

Tool Count1/5

33 tools is excessive for a server named 'Worldbank Projects', as only 3-4 tools directly relate to Worldbank data. The rest are generic Pipeworx utilities and unrelated domains, making the tool count inappropriate for the server's stated purpose.

Completeness1/5

For the domain of Worldbank Projects, only basic lookup and search tools are provided (search_projects, get_project, projects_by_country). Missing essential CRUD operations, filtering by sector/theme, or project lifecycle management. The server's tool surface is severely incomplete for its intended focus.