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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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses extensive behavioral traits: pairing_unverified is set whenever pairs are returned, legs with unknown metric_type/match_subtype are never paired, null temporal_alignment means 'could not be computed' rather than confirmed alignment, and the tool does not model Kalshi's fee schedule so all spreads are gross. It even reveals that compatibility warnings can be non-empty despite matched_pairs>0, which is a critical non-obvious behavior.

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 CAPS labels and dense with information, but it is very long and contains redundancy: the warning to read compatibility fields even when matched_pairs>0 is repeated, and the temporal_alignment null semantics are explained twice. While every paragraph adds value, tighter editing would improve scannability for an agent.

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?

For a tool with no output schema, the description is remarkably complete: it enumerates the return fields (top_spreads_pp, compatibility_warning, compatibility_codes[], flags[], temporal_alignment{}, fees_note, skipped_cross_type/subtype, low_confidence_pairs[]), explains the meaning of every compatibility code, and covers edge cases like null alignment and unknown leg types. An agent has enough context to invoke the tool and interpret its response correctly.

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 already has a description. The description adds meaningful semantic context by framing topic as a pre-mapped shortcut mode, explaining that explicit ticker/slug override the topic-mapped side, and stating that both modes run the identical token-overlap matcher. This enriches the agent's understanding of how the parameters interact beyond the schema's individual 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 description opens with a precise statement of purpose — "Cross-venue spread between Kalshi and Polymarket for the same resolving question" — naming both the resource (cross-venue spreads) and the behavior (computing/reporting them). It also distinguishes itself from siblings like polymarket_arbitrage and polymarket_edges by emphasizing the Kalshi–Polymarket cross-venue focus and the two operating modes.

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 clearly explains when to use each mode: topic shortcuts for 10 pre-mapped macros, and explicit kalshi_event_ticker + polymarket_event_slug for custom pairings. It also warns that most pre-mapped topics currently return compatibility_warning and that pre-mapped ≠ tradeable. However, it never explicitly names sibling tools as alternatives or states when NOT to use this tool versus those siblings, so the guidance is context-rich but lacks formal exclusions.

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

The tool set mixes general-purpose Pipeworx tools (ask_pipeworx, ai_visibility_check, bet_research) with only three paleontology-specific tools (find_fossils, get_taxon, list_subtaxa). Multiple similar 'ask_pipeworx' variants further blur distinctions, making it difficult for an agent to select the right tool without deep domain knowledge.

Naming Consistency3/5

Tool names are mostly in snake_case and somewhat descriptive, but the naming conventions vary widely: imperative verbs (find_fossils), interrogative (suggest_questions), and nouns (recent_alerts). The presence of multiple 'ask_pipeworx' variants with inconsistent suffixes (beta, grounded) adds confusion.

Tool Count2/5

With 34 tools, the server is oversized for its claimed paleontology focus. The vast majority of tools are unrelated to Paleobiology, making the server feel more like a general-purpose data API than a specialized paleontology tool. A focused server should have a smaller, targeted set.

Completeness2/5

For the Paleobiology Database purpose, the coverage is severely lacking: only three tools are directly relevant (find_fossils, get_taxon, list_subtaxa). Missing essential operations like searching taxa by name, retrieving occurrences by location, or accessing collections data. The tool set is not a coherent interface for the domain.