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Virustotal

by io.github.pipeworx-io

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. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "topic": "fed"
+  },
+  {
+    "topic": "btc"
+  }
+]
  2. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already mark the tool as readonly, open-world, idempotent, and non-destructive, and the description adds a large amount of behavioral detail: token-overlap matching, pairing_unverified, compatibility codes, unclassified-leg exclusion, non-modeled Kalshi fees, gross vs net spreads, and the precise meaning of null in temporal_alignment. Nothing contradicts the 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 well-structured with clear sections (TWO MODES, RESPONSE, SAFETY FIELDS, Codes) and front-loaded intent. All content is substantive, though some redundancy appears—for example, override behavior is stated in both the schema and the description, and pairing verification is emphasized multiple times.

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?

This is a high-complexity tool with no output schema, and the description compensates thoroughly by explaining response fields, compatibility codes, per-entry flags, skipped counters, fee semantics, and null behavior. An agent has enough information to invoke the tool correctly and interpret results safely.

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?

The input schema already covers 100% of the parameters, so the baseline is 3. The description adds meaningful semantics by explaining that topic auto-fetches mapped events, explicit ticker/slug overrides the mapped side, and that both modes run the identical token-overlap matcher. That is useful but not extensive, so it earns a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the resource ('cross-venue spread between Kalshi and Polymarket'), scopes it to the same resolving question, and outlines two modes. It is not a tautology and distinguishes the tool from generic single-venue queries, but it never contrasts sibling tools such as polymarket_arbitrage or polymarket_edges, so explicit sibling differentiation is missing.

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 strong context for when the spread is a real signal ('when the bet shapes are equivalent') and warns that pre-mapped topics are often not tradeable and usually produce compatibility warnings. It also explains the two invocation paths clearly, but it does not explicitly name alternatives or say 'use X instead' for related sibling tools.

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 set mixes several overlapping families: ask_pipeworx and ask_pipeworx_beta are described as currently identical, while ask_pipeworx_grounded, deep_research, bet_research, and validate_claim all route to the same underlying data sources. Polymarket tools (arbitrage, edges, edge_tracker, fill_risk, spread) also blur together; only the four lookup_* VirusTotal functions are cleanly distinct.

Naming Consistency3/5

Names are uniformly snake_case with a few consistent families (lookup_domain/file/ip/url, ask_pipeworx_*, polymarket_*), which helps. However, the set mixes imperative verbs (remember, forget, subscribe, validate_claim), noun phrases (entity_profile, deep_research, recent_alerts), and inconsistent prefixes, so no single naming convention holds across the server.

Tool Count2/5

35 tools is too many for the apparent purpose, especially for a server named Virustotal. The bulk of the tools address unrelated Pipeworx research, memory, and prediction-market functions, so the count does not reflect the server's advertised domain.

Completeness1/5

For a VirusTotal server, only four lookup tools exist and there is no way to submit a URL/file, create a scan, retrieve analysis details, or explore relationships—core VirusTotal operations are missing. Scoped broadly, the unrelated Pipeworx tools are extensive, but they do not fill the gaps in the advertised domain. The surface is severely incomplete relative to the server name.

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