list_exchangesTop cryptocurrency derivatives exchanges tracked by Coinfuty, with open interest, 24h volume, 24h liquidations, futures maker/taker fees, number of markets, and CMC rank.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It specifies the data fields returned, but does not explicitly state that the operation is read-only or non-destructive (though that is obvious from context). It also does not mention sorting, pagination, or any output format. The listing of metrics adds some transparency, but there are gaps.
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 a single, well-structured sentence that front-loads the main subject ('Top cryptocurrency derivatives exchanges tracked by Coinfuty') and follows with a concise list of relevant data points. Every word earns its place, with no fluff or repetition.
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?
Given the simplicity of the tool (no params, no output schema), the description is largely complete: it lists the data fields returned. However, it is ambiguous what 'Top' means (ranking criterion) and does not mention any limits or default sorting. For a list tool, this missing detail slightly reduces completeness but does not severely hamper usability.
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?
The tool has zero parameters and the schema coverage is 100%, so the baseline is 4 per the rubric. The description adds no parameter-related meaning because there are none, but it appropriately describes what the tool returns, which is sufficient. There is no need for additional parameter semantics.
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 tool as providing top cryptocurrency derivatives exchanges with specific metrics (open interest, volume, liquidations, fees, markets, CMC rank). While it lacks an explicit verb like 'list', the tool name 'list_exchanges' and the noun phrase 'Top cryptocurrency derivatives exchanges' make the action unambiguous. It distinguishes itself from siblings by focusing exclusively on derivatives exchanges, which is distinct from coin markets, summaries, and funding rates.
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 implies usage: it is for retrieving an overview of derivatives exchanges with specific data points. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Sibling tools like get_exchange_breakdown or get_market_overview could be confused, but the description provides enough context for an experienced agent to infer appropriate use.
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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Each tool targets a distinct data surface: list markets, single-coin summary, exchange breakdown, funding rates, market overview, price history, and exchange list. Even where data overlaps, the descriptions clearly delineate scope (e.g., get_coin_summary vs. get_funding_rates).
All tool names follow a consistent verb_noun pattern (get_* and one list_*), using clear, memorable resource nouns. No mixing of camelCase or inconsistent verb styles.
Seven tools is well-scoped for a crypto derivatives data API, providing enough granularity without bloat. Each tool earns its place and the count sits comfortably within the ideal range.
The surface covers current snapshots, historical time series, per-exchange breakdowns, funding details, market aggregates, and exchange metadata. No obvious dead ends or missing operations for the stated purpose.