Crypto Data & Market Analysis Agent

get_derivatives_aggregate

Read-onlyIdempotent

Watchlist sweep over up to 10 coins in one call: the headline funding and open interest figures per coin — average funding, total open interest in USD, funding spread — with no per-venue rows, which keeps the response compact enough to compare positioning across a basket. Costs a single upstream call no matter how many coins you request, so prefer it over repeated single-coin calls. Figures come from the major liquid venues — Binance, Bybit, OKX and Hyperliquid; thin venues are excluded, since their outlier rates would otherwise distort the average by an order of magnitude. Coins with no major-venue data are listed in "unavailable" instead of failing the whole request. Reach for get_derivatives instead when you need the per-venue detail on one coin. Funding is returned in PERCENT per 8 hours (0.0061 means 0.0061%, not 0.61%) and also ANNUALIZED as a percent per year — 0.0067% per 8h is 7.3% a year, which says immediately whether a long is paying more than a bond yields. Open interest is in USD. Current snapshot.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`coins`	No	Base coins, e.g. ["BTC","ETH","SOL"]. Maximum 10. Defaults to BTC and ETH.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`coins`	Yes
`unavailable`	Yes	Requested coins with no major-venue perpetual. Never silently dropped.

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, establishing safety. The description adds substantial behavioral context: costs a single upstream call, excludes thin venues to avoid outlier distortion, handles unavailable coins gracefully, and details the units (percent per 8h, annualized, OI in USD). This goes well beyond what annotations provide, and there is no contradiction.

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?

The description is well-structured, starting with a clear action statement, then explaining benefits, data sources, handling of missing data, units, and the alternative tool. Every sentence adds value. However, it is slightly verbose (multiple sentences on units could be condensed), preventing a perfect score.

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?

Given the tool's complexity (aggregate derivatives across multiple venues), the description covers all critical aspects: what data is returned (funding, OI, spread), how it is aggregated (no per-venue rows), data sources (Binance, Bybit, OKX, Hyperliquid), handling of unavailable coins, and units. The presence of an output schema means return value details are not needed, making this description complete.

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

Parameters5/5

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

Schema coverage is 100% (the one parameter 'coins' is fully described). The description adds value beyond the schema by explaining the maximum of 10 coins, the default (BTC and ETH), and the purpose of the parameter in the context of a basket sweep. Baseline 3 is exceeded due to this added context.

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 clearly states it performs a 'watchlist sweep' of up to 10 coins, returning headline funding and open interest figures aggregated across major venues. It explicitly distinguishes itself from the sibling `get_derivatives` by noting that tool provides per-venue detail, while this tool gives compact totals for comparison.

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

Usage Guidelines5/5

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

The description explicitly advises preferring this tool over repeated single-coin calls because it costs a single upstream call regardless of coin count. It also provides a clear alternative: 'Reach for get_derivatives instead when you need the per-venue detail on one coin.' Additionally, it explains that coins with missing data are listed as 'unavailable' rather than failing, guiding the agent on expected behavior.

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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TDQS

A4.2/5.0

Disambiguation4/5

Most tools target distinct domains (network, market, derivatives, macro, on-chain flows), and overlapping tools like get_derivatives vs get_derivatives_aggregate are clearly differentiated by scope and detail level. However, get_crypto_market and get_market_dominance both cover market-wide data, and get_btc_network and get_eth_whale_flows both touch on-chain activity, which could cause some confusion.

Naming Consistency5/5

All tool names follow a consistent get_ prefix with descriptive nouns (e.g., get_btc_network, get_defi_overview, get_execution_cost). The pattern is uniform across all 16 tools, with no camelCase or inconsistent verb styles, making it very predictable for an agent.

Tool Count5/5

With 16 tools, the server covers a broad but coherent domain of crypto market analysis—prices, on-chain, derivatives, macro, sentiment, and execution. Each tool addresses a distinct analytical need, and the count is well-scoped for a comprehensive agent, not excessive given the breadth of features.

Completeness4/5

The surface is remarkably complete for a market analysis agent, covering spot, derivatives, on-chain, macro, sentiment, history, and execution costs. Minor gaps exist: no direct tool for decentralized exchange (DEX) trading volumes or specific coin list discovery, and no tool for order book depth beyond the execution cost tool. However, agents can work around these with existing tools.

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