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DanielTomaro13

sportsdata-mcp

kalshi_orderbook

Retrieve the order book for any Kalshi market, showing resting yes and no bids by price level in dollars.

Instructions

Order book for one market — resting yes/no bids by price level (dollar-denominated).

Returns: {orderbook_fp:{yes_dollars:[[price, size], …], no_dollars:[[price, size], …]}} (empty arrays when nothing is resting)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
tickerYes
Behavior4/5

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

With no annotations, the description bears full burden. It discloses the return format in detail, including empty arrays when nothing is resting, and notes that prices are dollar-denominated. However, it does not state whether the data is a snapshot or live, nor any authentication requirements. Despite these omissions, the added value is substantial.

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 extremely concise: one sentence for purpose and a clear return format example. No redundant words. Front-loaded with the key action and resource.

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?

Given no output schema, the description provides a complete output format with explicit structure. It covers the key aspects of an order book tool. However, it could mention default depth behavior or limits, which would enhance completeness.

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 0%, so the description must compensate. It implies the 'ticker' parameter identifies the market (one market). However, it does not explain the 'depth' parameter (e.g., number of price levels or default behavior). The description adds meaning for one parameter but leaves depth ambiguous.

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 retrieves the order book for one market, specifying resting yes/no bids by price level. It distinguishes itself from sibling kalshi tools like kalshi_market (market details) and kalshi_candlesticks (price history) by focusing on order book depth. The verb 'returns' combined with the resource 'order book' provides a specific purpose.

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

Usage Guidelines2/5

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

The description lacks explicit guidance on when to use this tool versus alternatives like kalshi_market or kalshi_trades. It does not mention prerequisites, such as needing the market ticker, nor does it explain when the depth parameter is useful. No exclusions or conditions are provided.

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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