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AIsa Finance

Get Kalshi Trades

get_kalshi_trades
Read-onlyIdempotent

Get the executed-trade tape for Kalshi markets — actual fills, not quotes. Use this when you need realized prices and traded size over a window, for example to see how conviction moved while an event unfolded; narrow with ticker and the min_ts / max_ts Unix-second range, and set is_block_trade to isolate large negotiated trades.

Returns trades[] with trade_id, ticker, count_fp (contracts), yes_price_dollars / no_price_dollars, taker_side, and created_time, plus a cursor to page with.

For the current quotes, settlement rules, and market metadata rather than fills, use get_kalshi_markets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results per page. Defaults to 100. Maximum value is 1000.
cursorNoPagination cursor from the previous response.
max_tsNoFilter trades before this Unix timestamp.
min_tsNoFilter trades after this Unix timestamp.
tickerNoFilter by Kalshi market ticker.
is_block_tradeNoFilter trades by whether they are block trades. Omit to return all trades.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With annotations already marking this as read-only, idempotent, and non-destructive, the description adds useful behavioral context: it returns actual fills (not quotes), the list of fields, and the pagination cursor. It does not introduce unrelated claims and adds insight beyond 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 compact and purposeful, opening with the core purpose and then moving to usage guidance, return shape, and the sibling alternative. Minor redundancy with the output schema (detailed return fields) keeps it from a 5, but every sentence earns its place.

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?

With 6 parameters, full schema coverage, an output schema, and safe/read-only annotations, the description provides sufficient context for correct invocation. It covers the when-to-use, how-to-filter, and what-to-expect, while pointing to the relevant sibling tool. The only gap is lack of explicit mention of authentication/rate limits, but the annotations already signal a harmless read operation.

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?

Schema coverage is 100%, so the baseline is 3; the description adds value by explaining how parameters combine (narrow with ticker and time range, set is_block_trade to isolate large negotiated trades), which goes beyond the schema's simple per-field filters.

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 a specific action ('Get') on a specific resource ('executed-trade tape for Kalshi markets') and explicitly differentiates itself from quotes and from get_kalshi_markets, making it easy for an agent to distinguish from siblings.

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?

It explains when to use this tool ('when you need realized prices and traded size over a window'), gives concrete filtering guidance with ticker, min_ts/max_ts, and is_block_trade, and explicitly tells the agent to use get_kalshi_markets when quotes/settlement/metadata are needed instead.

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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