Skip to main content
Glama

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 readOnlyHint=true and destructiveHint=false, and the description is fully consistent with those. Beyond annotations, it discloses crucial runtime behavior: compatibility_codes, per-pair flags, skipped_unclassified handling, gross-vs-net spread via fees_note, temporal_alignment null semantics, and the pairing_unverified caveat. This is exemplary transparency for a complex comparison tool.

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-organized with clear labeled sections: TWO MODES, RESPONSE, SAFETY FIELDS, and Codes. Every section adds necessary behavioral context for a tool with no output schema. Some sentences are densely nested and could be tightened, but the front-loaded purpose and structured layout earn a solid score.

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 and high complexity, this description is exceptionally complete. It covers return values (leg-by-leg prices, top_spreads_pp, compatibility_warning/codes), per-pair flags, skipped-leg counters, temporal alignment semantics, fee caveats, and the unverified pairing warning. An agent has enough context to invoke the tool and interpret results correctly without further guessing.

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 schema already documents all three parameters. The description adds meaning beyond the schema by explaining the two modes, how topic maps to both venues, and how explicit parameters override the topic-mapped side. It also clarifies that both modes run the same token-overlap matcher, which is not apparent from the schema alone.

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 specific verb-resource pair: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' It clearly distinguishes this from siblings like polymarket_arbitrage or polymarket_edges by naming the exact two venues and the comparison being made. The description also makes clear it is a read/comparison tool, not a trade execution tool.

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 explicitly defines two usage modes — topic shortcuts versus explicit kalshi_event_ticker + polymarket_event_slug — and explains when each is appropriate. It cautions that 'pre-mapped ≠ tradeable' and that most topics return compatibility_warning today, which is valuable usage guidance. It does not explicitly name when to prefer a sibling tool over this one, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same 5,708 tools, with beta explicitly described as currently identical to the stable version. Prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage) also blur together, and the Notion tools are a small island in a sea of unrelated Pipeworx utilities.

Naming Consistency3/5

The names are uniformly lowercase with underscores, but conventions are mixed: some use verb-first patterns (ask_pipeworx, generate_llms_txt, scan_dependency), others are noun-phrases (entity_profile, recent_changes, polymarket_edges), and domain prefixes are inconsistent (notion_*, polymarket_*, pipeworx_*, but bare bet_research, compare_entities, recall). It is readable but lacks a coherent naming scheme.

Tool Count2/5

36 tools is already heavy, but the bigger issue is scope: the server is named Notion_connect yet only 5 of 36 tools relate to Notion. The rest span data research, prediction markets, memory, subscriptions, AI visibility, npm auditing, and llms.txt generation — a grab bag far beyond any single purpose, with multiple redundant meta-tools inflating the count.

Completeness2/5

As a Notion connector it is severely incomplete: there is no create/update/delete for pages or databases, and no way to write content back to Notion — only read/search/query operations. For the broader Pipeworx surface, the tool set is sprawling but unfocused, so it is hard to identify a coherent domain where coverage could be considered complete.