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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

kalshi_historical_cutoff

Returns Kalshi's three live-vs-historical cutoff timestamps—market_settled_at, orders_updated_at, trades_created_at—so you know when settled market data belongs in historical endpoints.

Instructions

Kalshi historical data cutoff. Returns the three cutoff timestamps Kalshi uses to split live from historical data: market_settled_at, orders_updated_at and trades_created_at. Use them to decide when settled market data should be read from the historical endpoints. Takes no parameters.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the call is parameterless and returns three named timestamps, which signals a safe read, but says nothing about whether the cutoff values shift over time, their timestamp format, or caching/rate behavior.

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?

Three tight sentences with the purpose front-loaded, followed by the returned fields and then the usage guidance. No redundant restatement of the name and no filler.

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 exists, so the description correctly names the three returned fields and their role. It omits the timestamp format and any indication of how often the cutoffs change, a minor gap for a no-parameter informational tool.

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?

Zero parameters, so the baseline is 4. The description reinforces this with 'Takes no parameters,' which is the relevant detail for an agent deciding how to call it, and there is nothing further to document.

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?

States a specific verb and resource ('Returns the three cutoff timestamps Kalshi uses to split live from historical data') and enumerates exactly which fields come back. An agent can tell this apart from sibling tools like kalshi_historical_trades or kalshi_exchange_status without opening a schema.

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?

Explicitly says 'Use them to decide when settled market data should be read from the historical endpoints,' which gives a clear usage context and implicitly routes to historical siblings. It stops short of naming a specific alternative tool or stating when not to call it, so not a 5.

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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