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DanielTomaro13

sportsdata-mcp

kalshi_series_list

Read-onlyIdempotent

Retrieve all series in a specified category, like Sports or Politics. Returns ticker, title, frequency, and settlement sources for each series.

Instructions

All series in a category (Sports, Politics, Economics, Financials, Climate and Weather, Entertainment, …) — the top of the id chain.

Returns: {series:[{ticker, title, category, frequency, tags, settlement_sources, contract_url}]}

Example: Every sports series {"category": "Sports"}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesSeries category (e.g. Sports).
include_product_metadataNoEmbed product metadata.
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable context by stating 'Auth: none needed' and specifying the exact return fields. This goes beyond the annotations without contradicting them.

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?

The description is compact, with a clear primary statement, a return structure snippet, a helpful example, and an auth note. Every sentence adds value and the example improves comprehension without redundancy.

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?

For a simple two-parameter tool with no output schema, the description covers purpose, return format, example usage, and authentication. It's sufficiently complete for an agent to invoke it correctly.

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 description coverage is 100%, with both parameters already described. The description adds an example usage for 'category' but doesn't elaborate on 'include_product_metadata', so it's at baseline for schema-driven semantics.

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 description clearly states the tool lists all series in a category, giving a specific verb-resource relationship. It differentiates from siblings like kalshi_series by noting it's at the 'top of the id chain' and uses 'All series in a category'.

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 provides clear context with example categories and an explicit usage example (Sports category). It doesn't name alternatives or list when-not-to-use, but the hierarchy hint and return structure imply its role among siblings.

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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