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Ironflow: Hyperliquid data

List cohorts

list_cohorts
Read-only

List available address cohorts: six predefined groups (top_pnl_30d, high_volume_30d, whale_fills, net_withdrawers_7d, liquidation_prone, vault_whales) plus any custom cohorts the caller has created

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
dataNoCohorts
noticeNoPresent when the API added a note: how a market name was read, that data starts later than asked because of the history window, or a next step such as a free key

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

The readOnlyHint and openWorldHint annotations already cover the safety and openness profile. The description adds useful scope detail by enumerating the predefined cohorts and mentioning caller-created custom cohorts, but it does not discuss access constraints, pagination, or ordering behavior. With annotations present, this is adequate but not rich beyond structured data.

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

Conciseness5/5

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

The description is a single front-loaded sentence with no wasted framing. The enumerated cohort names are specific and useful for an agent trying to recognize the resource.

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 no input parameters and an output schema present, the description need not explain return values. It gives enough context for a simple catalog listing, though it could more explicitly position this tool relative to get_cohort_addresses.

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?

The tool has zero parameters, so parameter semantics are essentially not applicable. The schema coverage is 100% and the baseline for zero-parameter tools is 4.

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?

The description states a specific verb and resource: listing available address cohorts. It also enumerates the six predefined cohorts and notes that caller-created custom cohorts are included, making the scope clear. It does not explicitly name or differentiate itself from the sibling get_cohort_addresses, so it falls short of full sibling differentiation.

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

Usage Guidelines3/5

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

Usage is only implied: an agent can infer this is the discovery step before fetching cohort addresses. The description does not explicitly say when to use this tool versus get_cohort_addresses or how the two are meant to be sequenced.

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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