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xch1tbllc

storm-mcp

by xch1tbllc

storm_list_events

Lists prediction-market events tracked across public venues. Filter by category or status to find open or resolved events before drilling into specifics.

Instructions

List canonical prediction-market events (questions/topics) tracked by Eyewall Markets / Storm across the public venues it covers (Kalshi, Polymarket, Manifold, ForecastEx, and others). Use this to discover what events exist before drilling into a specific event with storm_get_event. Supports filtering by category (e.g. 'politics', 'economics') and status (e.g. 'open', 'resolved'), and is cursor-paginated. Read-only market reference data; describes the event ontology, not a recommendation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size (1-100). Default server-side is typically 25.
cursorNoOpaque pagination cursor returned in next_cursor from a previous call.
categoryNoFilter to a single category slug, e.g. 'politics'.
statusNoFilter by event status, e.g. 'open' or 'resolved'.
Behavior4/5

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

No annotations provided, but description declares 'Read-only market reference data' and mentions cursor-pagination. Lacks details on rate limits or auth, but sufficient for basic safety.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, front-loaded with purpose, each sentence adds value (use case, filtering, pagination, read-only nature). No fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description mentions cursor-paginated results. Could specify return fields, but adequate for discovering events before drilling down.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. Description adds examples for category and status, but no deeper semantics beyond schema descriptions.

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?

Description clearly states the tool lists prediction-market events with specific venues (Kalshi, Polymarket, etc.), uses the verb 'list' and resource 'events', and distinguishes from sibling tool storm_get_event.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this to discover what events exist before drilling into a specific event with storm_get_event', providing a clear use case and alternative.

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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