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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?

This is exceptionally transparent. It discloses that spreads are gross and do not model Kalshi fees, that unknown legs are never paired, that null temporal_alignment means 'could not be computed' rather than aligned, and it enumerates all compatibility codes and skipped-leg counters. This goes far beyond the read-only and idempotent annotations.

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 for a tool with no output schema and many safety-related edge cases, nearly every sentence adds needed information. It is structured into purpose, modes, response summary, safety fields, fee note, and skipped-leg counting. It is not as minimal as it could be, but it earns its length.

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 burden of explaining return behavior, and it does so thoroughly: response fields, per-pair flags, compatibility codes, fee treatment, null semantics, skipped comparisons, and limitations. An agent has enough context to invoke the tool appropriately and interpret ambiguous results.

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 already 100%, but the description adds real semantic value by explaining the two modes, the meaning of the topic shortcut list, and that explicit ticker/slug arguments override the topic-mapped side. It also clarifies that both modes use identical matching logic, which is useful behavior not inferable 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 states a specific function: reporting the cross-venue spread between Kalshi and Polymarket for the same resolving question. It goes beyond a vague label by explaining the signal quality and distinguishing tradeable vs. non-tradeable spread, which clearly separates it from related sibling concepts.

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 within-tool guidance: two modes ('topic' shortcuts vs explicit ticker/slug), the fact that both modes share the same matcher, and strong warnings that pre-mapped shortcuts often return compatibility warnings and are not automatically tradeable. It does not explicitly contrast the tool with sibling alternatives like polymarket_arbitrage or polymarket_edges, but the context of use is otherwise very clear.

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
Disambiguation2/5

Many tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer queries, and the multiple polymarket_* tools scan for edges and arbitrage. The Drive tools are distinct, but the surrounding 31 unrelated tools create significant ambiguity about which tool to call for a given task.

Naming Consistency2/5

Tool names are all snake_case, but the pattern is inconsistent: some start with verbs (drive_create_file, ask_pipeworx, validate_claim), some are noun phrases (entity_profile, recent_changes, polymarket_edges), and some are bare verbs (remember, forget, recall). There is no uniform verb_noun convention, and suffixes like _beta and _grounded add further irregularity.

Tool Count1/5

36 tools is far too many for a server named Google_drive, especially since only 5 tools (drive_create_file, drive_get_content, drive_get_file, drive_list_files, drive_search) actually relate to Drive. The other 31 tools cover unrelated domains like Pipeworx data queries, Polymarket betting, and memory management, making the tool count wildly disproportionate to the server's apparent purpose.

Completeness2/5

For a Google Drive server, the tool set is incomplete: it covers create, get content, get metadata, list, and search, but lacks essential operations like updating, deleting, uploading, moving, copying files, creating folders, or managing permissions/sharing. These gaps would force agents to work around missing core Drive functionality.