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Google_search_console

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 mark it readOnly/idempotent/non-destructive, and the description layers substantial behavior on top: matching is token-overlap not a shared resolution source, unknown metric_type/match_subtype legs are never paired, temporal_alignment null semantics, and Kalshi fees are not modeled. It also flags conditional disclosures ('BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0'). No contradiction with 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 earns its length: it has no filler and every block (response, safety fields, codes, fees, skipped counters) carries a distinct operational warning. It front-loads the core purpose and then uses labeled sections. A few repetitions (e.g., temporal_alignment_unknown appears twice) mean it is not maximally tight.

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 contract documentation and does so thoroughly: response shape, safe-vs-warning fields, per-entry flags, null semantics, fee grossness, and skipped leg counters are all specified. An agent has enough to interpret results and know when a spread is not tradeable.

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 already covers all three parameters 100%, including examples and override notes. The description adds useful interaction semantics – both modes run the identical token-overlap matcher and explicit ticker/slug override the topic-mapped side. This earns a bit above baseline, though much of the parameter meaning is already in the schema.

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?

Opens with a specific verb+resource: computes cross-venue spread between Kalshi and Polymarket for the same resolving question. It names the two venues and the core output (top_spreads_pp, Kalshi − Polymarket), which clearly distinguishes it from the other polymarket_* siblings. The two-mode explanation also makes the purpose concrete.

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?

Explicitly distinguishes the `topic` shortcut mode from the explicit `kalshi_event_ticker` + `polymarket_event_slug` mode, so an agent knows how to choose inputs. It gives honest when-not-to-trust guidance ('Real cross-venue spreads are rarer… pre-mapped ≠ tradeable', spread_pp is gross not net). It does not, however, name sibling alternatives like polymarket_arbitrage or state when to prefer them, which keeps this at 4 rather than 5.

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

A3.5/5.0
Disambiguation2/5

The set has several overlapping clusters: ask_pipeworx and ask_pipeworx_beta are explicitly identical, multiple polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) occupy the same prediction-market space, and ai_visibility_check/scan_competitor_ai_presence are near-duplicates. A few tools (memory triad, gsc_* calls) are crisp, but the boundaries between the meta-research tools (ask_pipeworx, deep_research, discover_tools, validate_claim) are not obvious enough to prevent misselection.

Naming Consistency2/5

Naming is a mixed bag: some tools follow snake_case verb_noun (gsc_list_sites, resolve_entity, search_within), others are lowercased concatenations (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and several are bare nouns or adjectives (recent_alerts, forget, recall, process). There is no consistent verb style or separator convention across the set.

Tool Count1/5

35 tools is already heavy, but the bigger problem is that only 4 of them (gsc_list_sites, gsc_list_sitemaps, gsc_inspect_url, gsc_search_analytics) relate to the server's stated Google Search Console purpose. The remaining 31 are a sprawling Pipeworx data/prediction-market/memory toolkit, making the count wildly disproportionate to the apparent scope.

Completeness1/5

For a Google Search Console server, the surface is severely incomplete: it can list sites/sitemaps, inspect URLs, and query analytics, but lacks sitemap submission, property add/remove, URL removal/access control, and other core GSC operations. Conversely, the 31 off-domain tools make the domain itself incoherent — an agent cannot tell what this server is actually for.