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Macro & Commodities Desk

Kalshi Perps Board — price, leverage and funding for every perp

perps_board
Read-only

Use for "Kalshi perps funding rate" and "how much leverage on Kalshi gold perps". Every Kalshi perpetual future: price, 24h volume, open interest, max leverage long and short, funding cadence, and what funding has cost a long since launch. Pass asset ("btc", "gold") for one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetNoOne perp: symbol or name ("btc", "gold", "XAG").
limitNoMax rows (default 25). Values above 30 are clamped to 30.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNoKalshi perps: price, 24h volume, open interest, max leverage, funding.
as_ofNoWhen the board was read.
sourcesNo
tell_userNoShow this sentence to the user first.
timestampNo
needs_inputNo
example_callNo
data_freshnessNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / limit / anyOf
      Removed value: -[
      -  {
      -    "anyOf": [
      -      {
      -        "type": "number"
      -      },
      -      {
      -        "type": "string"
      -      }
      -    ]
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • addedInput schema / properties / limit / type
      Added value: +[
      +  "number",
      +  "string",
      +  "null"
      +]
  2. Changed6 schema fields changed
    • addedInput schema / properties / limit / anyOf
      Added value: +[
      +  {
      +    "anyOf": [
      +      {
      +        "type": "number"
      +      },
      +      {
      +        "type": "string"
      +      }
      +    ]
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedInput schema / properties / limit / default
      Removed value: -25
    • changedInput schema / properties / limit / description
      Previous value: -"Max rows (default 25)."New value: +"Max rows (default 25). Values above 30 are clamped to 30."
    • removedInput schema / properties / limit / maximum
      Removed value: -30
    • removedInput schema / properties / limit / minimum
      Removed value: -1
    • removedInput schema / properties / limit / type
      Removed value: -"integer"
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "additionalProperties": {},
      +  "properties": {
      +    "as_of": {
      +      "description": "When the board was read."
      +    },
      +    "data_freshness": {},
      +    "example_call": {},
      +    "needs_input": {},
      +    "rows": {
      +      "description": "Kalshi perps: price, 24h volume, open interest, max leverage, funding."
      +    },
      +    "sources": {},
      +    "tell_user": {
      +      "description": "Show this sentence to the user first.",
      +      "type": "string"
      +    },
      +    "timestamp": {
      +      "type": "string"
      +    }
      +  },
      +  "type": "object"
      +}
  4. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds real value beyond that by disclosing the return payload's shape, including a derived metric (cumulative funding paid by a long since launch) and the fact that all perps are returned by default.

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?

Three sentences, front-loaded with usage triggers before the field inventory, with no filler sentences. The field enumeration is long but each item earns its place by telling the agent what data comes back.

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?

With an output schema present, the return values need not be described, and the read-only/open-world annotations cover safety. The description still supplies enough context (default full-board behavior, asset narrowing, funding-cadence framing) that an agent can invoke it confidently; only an explicit sibling tie-breaker is missing.

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 description coverage is 100%, so both parameters are fully documented in the schema, including the limit clamp at 30. The description repeats the asset examples ("btc", "gold") but adds no syntax or format detail the schema lacks, making the baseline 3 appropriate.

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 resource and enumerates exactly what the board contains: price, 24h volume, open interest, max leverage long/short, funding cadence, and cumulative funding cost for longs. An agent can distinguish this from siblings like perp_liquidation (liquidation events) or calculate_ev 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?

Opens with concrete user-phrasing triggers ("Kalshi perps funding rate", "how much leverage on Kalshi gold perps") and tells the agent how to narrow the result by passing an asset. It stops short of naming an alternative or stating when-not-to-use (e.g., versus perp_liquidation), so it is clear context without exclusions.

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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