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New and delisted perpetual contracts

get_new_listings
Read-only

Track newly listed and delisted perpetuals across all exchanges. Discover which exchange listed a coin first and stay informed on delistings with hourly scan data.

Instructions

Call this when the user asks what new perpetuals were listed, which exchange listed a coin first, or about delistings. Returns listings and delistings across every exchange the hourly scan covers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoWindow in days, 1-30 (default 30). Longer listing history is the listings dataset at bykaranteli.com/data.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.27.2
    • changedInput schema / properties / days / description
      Previous value: -"Window in days, 1-30 (default 30). Longer listing history is the paid x402 dataset."New value: +"Window in days, 1-30 (default 30). Longer listing history is the listings dataset at bykaranteli.com/data."
  2. Addedv0.9.0

TDQS

A4.3/5.0
Behavior4/5

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

The readOnlyHint and openWorldHint annotations already establish the safety profile, so the bar for behavioral disclosure is lower. The description adds useful operational context by stating that the tool returns both listings and delistings and that its scope is 'every exchange the hourly scan covers.' It does not describe return shape, but that is reasonable for a simple list-returning tool.

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?

Two sentences with no filler. Trigger conditions are front-loaded, followed by a compact statement of what the tool returns and its coverage scope.

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?

For a read-only tool with one optional parameter, the description provides the necessary invocation context: when to call it, what it returns, and over what exchange coverage. The absence of an output schema is acceptable because the description clearly summarizes the returned content as listings and delistings.

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?

The top-level description does not elaborate on the days parameter, but the input schema fully documents it: integer range 1-30, default 30, plus a pointer for longer listing history. With 100% schema description coverage, the baseline of 3 applies and no additional parameter explanation is required.

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?

The description opens with explicit trigger conditions ('Call this when the user asks what new perpetuals were listed, which exchange listed a coin first, or about delistings') and names the exact resource: new and delisted perpetual contracts across exchanges. This clearly differentiates it from the many sibling data tools like get_funding_heatmap or get_venue_markets.

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?

It provides explicit call conditions tied to concrete user intents, so an agent knows when to invoke it. It does not explicitly say when not to use it or name alternative tools, which keeps it just below a perfect score.

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