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kalshi_events

Retrieve normalized Kalshi event data from public market JSON. Filter by category, status, series ticker, and more.

Instructions

Kalshi events. Returns normalized Kalshi event rows from credential-free public market-data JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoKalshi category filter
cursorNoPagination cursor from a previous Kalshi response
limitNoRows to return, default 25, max 200
min_close_tsNoMinimum event close Unix timestamp in seconds
min_updated_tsNoMinimum event update Unix timestamp in seconds
series_tickerNoKalshi series ticker filter
statusNoEvent status filter
with_milestonesNoInclude event milestones when supported upstream
with_nested_marketsNoInclude nested market rows when supported upstream
Behavior2/5

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

With no annotations, description fully responsible for behavioral disclosure. It notes the tool is credential-free, which is a key trait. However, it does not mention that it is read-only (implied from public data but not explicit), rate limits, data freshness, or response format limitations. Lacks transparency for a data retrieval tool.

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?

Two short sentences, no redundant words. Front-loaded with tool name and output description. However, it is almost too concise, lacking details that could be added without becoming verbose.

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

Completeness2/5

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

Given the tool has 9 parameters, no output schema, and many similar siblings, the description is insufficient. It does not explain what 'normalized' means, what fields are returned, or how the filters in the schema interact. Without an output schema, more explanation is needed.

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 coverage is 100% (all 9 parameters described in input schema). The description adds no additional parameter meaning beyond the schema, so baseline score of 3 is appropriate.

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

Purpose4/5

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

States that the tool returns 'normalized Kalshi event rows' from credential-free public data. Clearly identifies the resource (events) and action (returns rows). However, does not distinguish from sibling tools like kalshi_event (singular) or kalshi_event_history, leaving ambiguity about whether it lists events.

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?

Mentions 'credential-free public market-data' implying use for public data, but provides no explicit guidance on when to use this tool versus alternatives like kalshi_event, kalshi_event_history, or other event-related tools. No when-not-to-use or prerequisites stated.

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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