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kalshi_get_candles

Read-only

Hourly OHLC candles (yes bid, yes ask, traded price) plus volume and open interest for a Kalshi market. This is the only history that exists for non-crypto Kalshi markets — Kalshi serves no historical order book — and it reaches back up to a year, far past the order-book capture. price is null in periods with no trade. Requires a paid plan; history gated by plan window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size (1–500).
cursorNoOpaque pagination cursor from a previous response's pagination.next_cursor.
tickerYesExact Kalshi market ticker from kalshi_search_markets (never constructed from a timestamp).
end_timeNoEnd of time as ms-epoch or ISO-8601. History is clamped to your plan's window.
intervalNoCandle period. Only 1h (60m) is recorded; omit for the default.
start_timeNoStart of time as ms-epoch or ISO-8601. History is clamped to your plan's window.

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the bar for disclosure is lower. The description goes beyond annotations by explaining that this is the only historical data source, that price is null when no trade occurred, and that history is gated by the paid plan's window. These are meaningful behavioral traits not present in 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.

Conciseness5/5

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

The description is two sentences, front-loads the essential information, and every clause adds value. It avoids redundancy with the schema and annotations while covering important caveats like pricing, history availability, and plan restrictions.

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 read-only data tool with 100% parameter coverage and no output schema, the description is remarkably complete. It tells the agent what data is returned (OHLC, volume, open interest), the null-price edge case, the time reach, and the paid-plan gating. There is no ambiguity about what to expect from the tool.

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?

The input schema covers all six parameters with descriptions (100% coverage). The description itself adds no additional parameter semantics beyond what the schema already provides, so the baseline of 3 is appropriate. It correctly mentions the clamping behavior but that is also in the parameter 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?

The description opens with a specific verb+resource: 'Hourly OHLC candles... for a Kalshi market' and explicitly lists the fields (yes bid, yes ask, traded price, volume, open interest). It also distinguishes itself from sibling orderbook tools by stating that this is the only history that exists and that Kalshi serves no historical order book.

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 clearly implies when to use this tool: whenever historical candle data for a Kalshi market is needed, as it is the only available history and extends up to a year. It contrasts with orderbook tools, but does not explicitly say 'use this instead of orderbook for historical data' or mention alternatives by name. However, the context is sufficient for an agent to infer the correct choice.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, clearly separated by venue prefix (kalshi_, limitless_, polymarket_) and action (get_orderbook, get_snapshots, search_markets). The screener and whoami tools are unique and not overlapping with any other tool.

Naming Consistency4/5

Most tools follow the venue_verb_noun pattern (e.g., kalshi_get_orderbook, polymarket_get_snapshots). However, polymarket_all_markets uses 'all' instead of a verb, and screener/whoami deviate entirely from the pattern, causing minor inconsistency.

Tool Count5/5

With 12 tools covering three venues plus cross-venue and session info, the count is well-scoped. Each tool serves a clear role without unnecessary bloat or deficiency.

Completeness4/5

The tool surface covers the core data retrieval operations (orderbook, snapshots, search, single market) for all venues. Missing are update/delete operations but those are outside the data provider scope. A minor gap is the lack of a dedicated 'get_market' for Kalshi and Limitless, though search_markets provides similar info.

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