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Wynncraft

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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds substantial behavioral detail beyond them: pairing_unverified keyword matching, compatibility_codes semantics, null temporal_alignment meaning, unclassified legs never being paired, and the gross-fee disclosure. This is far richer than the annotations alone and directly manages user expectations.

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 lengthy but information-dense and well-labeled with sections like TWO MODES, RESPONSE, SAFETY FIELDS, and Codes. It is front-loaded with purpose and usage, and most of the length is justified because there is no output schema and many safety and matching semantics need explanation.

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?

Despite having no output schema, the description documents the key response components—top_spreads_pp, compatibility_codes, temporal_alignment, skipped_unclassified, low_confidence_pairs, fees_note—and their meanings. It also covers important interpretive caveats such as compatibility_warning being non-empty even with matched pairs and temporal_alignment_unknown not meaning alignment.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description adds meaningful semantics beyond the schema: the full list of topic shortcut values, the override behavior of the explicit parameters, examples of ticker and slug formats, and the fact that both modes run the identical matcher. This makes each parameter's role in pairing unambiguous.

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 defines a precise, specific result: a cross-venue spread between Kalshi and Polymarket for the same resolving question, with the delta direction explicitly stated as Kalshi − Polymarket. The description distinguishes this from the polymarket-only siblings in the tool list by centering on cross-venue comparison and matching logic.

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 explains the two invocation modes—pre-mapped topic shortcuts and explicit ticker + slug pairings—and the conditions under which the spread is meaningful ('when the bet shapes are equivalent... when they aren't the tool says so'). It does not explicitly name alternative tools or state when to prefer another sibling such as polymarket_arbitrage, but the usage context 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

B3.1/5.0
Disambiguation2/5

The set is split between Wynncraft game data tools and a large Pipeworx data cluster, and within the Pipeworx cluster there is heavy overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (the beta is currently identical), ai_visibility_check and scan_competitor_ai_presence do essentially the same thing at different granularities, and six polymarket_* tools cover overlapping prediction-market functionality. An agent would frequently struggle to choose the right tool.

Naming Consistency3/5

Snake_case with a mostly verb_noun pattern dominates (ask_pipeworx, compare_entities, resolve_entity, validate_claim), and families like polymarket_* and pipeworx_* are internally consistent. However, there is a notable mix of noun-only tools (guild, item_database, leaderboard, player, news) and the server is named Wynncraft while the majority of tools are Pipeworx-branded, which breaks overall coherence.

Tool Count2/5

40 tools is well beyond the borderline range, and the count is inflated by redundancy: multiple ask_pipeworx variants, several overlapping polymarket tools, a memory trio, and subscription management that arguably belong to a separate server. The Wynncraft portion alone would be nicely scoped (~9 tools), but the merged surface feels heavy and unfocused.

Completeness4/5

The Wynncraft side offers solid read coverage of players, guilds, items, leaderboards, news, and online status, which is appropriate for the domain. The Pipeworx side covers lookup, grounded verification, comparison, research, prediction markets, subscriptions, memory, and feedback, leaving few obvious dead ends for the stated meta-purposes.

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