kalshi_candlesticks

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

With no annotations, the description conveys the return structure and basic behavior. However, it does not address error cases, data availability, or the mapping of period_interval to period labels, leaving some behavioral ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is very concise with two efficient sentences that front-load the purpose and provide the return structure. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the return structure is included, the description lacks explanation for all five parameters. For a data retrieval tool, parameter guidance is essential for correct usage, making it moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description only implicitly mentions ticker. It does not explain seriesTicker, start_ts, end_ts, or the meaning of period_interval default=60. The return format is shown but parameter meanings are not clarified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns OHLC candlesticks for one market over a time window, specifying supported periods (1m/1h/1d). It also provides the return structure. This distinguishes it from siblings like kalshi_candlesticks_batch.

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

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

The description implies usage for single-market candlestick data but does not explicitly mention when not to use it or alternatives (e.g., batch variant). It also lacks prerequisites or context about required identifiers.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.