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Seo Competitors

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?

Beyond the readOnly/idempotent annotations, the description discloses substantial runtime behavior: identical matcher behavior in both modes, compatibility code semantics, unclassified legs never being paired, skipped counters, and the standing fee caveat. This is far richer than the annotations alone and helps an agent trust and interpret output.

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 densely organized: purpose, modes, response, safety fields, fees, and limitations. It front-loads the core definition and uses clear labels like RESPONSE and SAFETY FIELDS. It earns its length because there is no output schema to carry the field-level detail, but it still demands effort to parse.

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, and it largely succeeds: it documents response contents, safety flags, per-leg skip behavior, fee treatment, and caveats about pre-mapped topics. An agent has enough context to decide whether to call the tool and how to interpret returned pairs.

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 meaning by explaining the topic shortcut list, the override semantics of kalshi_event_ticker and polymarket_event_slug, and the guarantee that both modes run the same token-overlap matcher. This clarifies parameter interaction beyond 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?

The first sentence names the deliverable exactly: a cross-venue spread between Kalshi and Polymarket for the same resolving question. It quickly distinguishes itself from single-venue sibling tools by emphasizing the two-venue comparison and the delta interpretation. The purpose is unambiguous and specific.

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 defines two entry modes and when to use each: topic shortcuts for pre-mapped macros, and explicit ticker/slug for custom pairings. It also warns that pre-mapped topics often return compatibility warnings and that the spread is gross not net. It does not name sibling alternatives explicitly, so it falls short of full when-not-to-use guidance.

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

A3.8/5.0
Disambiguation2/5

Several tools are near-duplicates or easily confused: ask_pipeworx_beta is explicitly identical to ask_pipeworx, ai_visibility_check overlaps with scan_competitor_ai_presence, and polymarket_edges, polymarket_arbitrage, and bet_research all target opportunity discovery. While many tools are distinct, the boundaries between these clusters are unclear enough to cause misselection.

Naming Consistency4/5

The vast majority of tools use a consistent lowercase snake_case convention with descriptive noun/verb patterns (e.g., polymarket_edges, entity_profile, validate_claim, resolve_entity). Minor deviations like seo_domain_ranked_keywords and ask_pipeworx_beta are slightly off-pattern, but the overall style is predictable.

Tool Count2/5

32 tools is above the threshold where a set starts to feel bloated, especially for a server named "Seo Competitors". The count includes many unrelated subsystems—Polymarket betting, memory, subscriptions, and generic data routing—making it feel like a kitchen sink rather than a focused SEO competitor toolkit.

Completeness2/5

For a server claiming to support SEO competitor analysis, the surface is incomplete: it offers a keyword-ranking tool and AI visibility checks, but lacks standard competitor SEO capabilities like backlink analysis, rank tracking over time, content-gap analysis, or site audits. The broader data/query tooling is extensive, but it doesn't fill the gaps in the advertised domain.