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Glama

Exchange insurance funds: size, 24h and 7d change, fund against open interest, daily history

get_insurance_funds
Read-only

Retrieve exchange insurance fund balances in USD, per asset, with 24h and 7d changes and share of perpetual open interest to assess liquidation buffers and compare venues.

Instructions

Call this when the user asks how big an exchange's insurance fund is, whether a fund is shrinking or was used after a crash, how much exchanges hold to absorb bankrupt liquidations, or how a fund compares with the venue's open interest. Returns the latest hourly reading per covered venue (every exchange the insurance fund board lists): the fund in USD (OKX's own published total, the sum of priced pools elsewhere), per asset, 24h and 7d change, the fund as a percent of the venue's perpetual open interest on the coins ByKaranteli tracks, and daily closes per venue. Set pools to include every pool row (the contracts it covers, asset, balance, USD). A fund is a balance the venue reports, not an audit of its reserves.

Input Schema

NameRequiredDescriptionDefault
poolsNoInclude every pool row (large for Binance and Bybit). Default false.
venueNoOne venue; omit for every covered venue.
history_daysNoDays of daily closes (default 30, max 366).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.1.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv0.29.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint, yet the description adds substantial context beyond them: data is a latest-hourly reading per venue, coverage spans every exchange on the insurance fund board, USD figures are OKX's own published total versus summed priced pools elsewhere, and a caveat that 'a fund is a balance the venue reports, not an audit of its reserves.' That precision and the methodological caveat are genuinely useful for interpreting results.

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?

Front-loads the trigger scenarios, then the return shape, then the one parameter nuance and a caveat — a logical order with no filler. The single long paragraph is dense; breaking the return inventory into a tighter clause list would improve scannability slightly.

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?

With no output schema, the description carries the full burden of explaining returns — and it does, covering the metric set, the venue coverage, the hourly cadence, and the per-venue daily history. An agent has everything needed to decide and invoke.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3, but the description adds meaning: it explains exactly what 'pools' unlocks (contracts covered, asset, balance, USD) beyond the schema's terse 'large for Binance and Bybit' note. It also ties history output to 'daily closes per venue' without contradicting the schema's 1-366 day range.

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 verb+resource (retrieve exchange insurance fund data) and enumerates the exact metrics returned: fund size in USD, per asset, 24h/7d change, percent of perpetual open interest, and daily closes. This is clearly distinguishable from siblings like get_open_interest or get_venue_profile.

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 explicit trigger conditions ('Call this when the user asks how big... whether a fund is shrinking or was used after a crash... how much exchanges hold to absorb bankrupt liquidations... how a fund compares with open interest'). It does not name a specific alternative sibling to use instead for the underlying OI data, but the when-to-use context is unambiguous.

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