Retrieve Kalshi orderbook for a ticker as YES-book bid/ask with raw ladders for market depth analysis.
Kalshi orderbook for a ticker, normalised to a YES-book bid/ask view (Kalshi publishes bid ladders only; asks are derived as 1 - NO bid). Raw ladders included.
| Name | Required | Description | Default |
|---|---|---|---|
| depth | No | ||
| ticker | Yes |
Changes observed during successful MCP inspections.
v0.18.1Output schema / (root)Previous value: -{
- "properties": {
- "result": {
- "title": "Result",
- "type": "string"
- }
- },
- "required": [
- "result"
- ],
- "title": "kalshi_get_orderbookOutput",
- "type": "object"
-}New value: +nullv0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds substantial behavioral detail beyond that: normalization to a YES-book bid/ask view, the fact that Kalshi publishes bid ladders only, asks derived as 1 - NO bid, and raw ladders included. No contradiction with annotations.
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 two concise sentences with no filler. It front-loads the core purpose and then adds the critical normalization detail. Every sentence earns its place.
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?
The description explains the core normalization behavior well, but with no output schema it does not describe the return structure, and it omits depth semantics. Given the strong annotations and read-only nature, it is adequate but leaves meaningful gaps for an agent invoking the tool.
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 description coverage is 0%, so the description must compensate. It clarifies the ticker parameter ('for a ticker') but says nothing about depth, its default, or how it affects the orderbook. This leaves an important parameter semantically undocumented.
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 identifies the resource ('Kalshi orderbook for a ticker') and adds valuable specificity about the normalized YES-book view and derived asks. However, it does not explicitly differentiate this from sibling orderbook tools like watch_book or the generic get_orderbook.
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 gives no explicit guidance about when to use this tool versus alternatives, and it does not mention any exclusions or sibling tools. The only implied usage context is that it is Kalshi-specific.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.