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ETF Flows

catalysts_etf_flows
Read-only

Recent daily spot-ETF net flows (USD) for an underlying asset (BTC, ETH, SOL, XRP; defaults to BTC): latest day total, per-fund breakdown, and the trailing daily trend. Positive means net inflows. Flows settle behind spot and skip weekends, so the latest row is routinely a day or more old — its age is reported next to the date, and the price it carries is the price on THAT date, not spot. 'symbol' is accepted as an alias for 'asset'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetNoUnderlying asset symbol, e.g. "BTC" or "ETH". Defaults to BTC.
symbolNoAlias for 'asset'.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses meaningful behavioral traits: data is delayed, weekends are skipped, the latest row's age is reported, and the attached price is from that date rather than current spot. This gives the agent critical expectations about data freshness and semantics.

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?

Three dense, well-ordered sentences: the core purpose and result shape come first, followed by essential caveats and the alias note. There is no filler or repetition of schema details that don't add value.

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?

Even without an output schema, the description gives a sufficient picture of what the tool returns: total, per-fund breakdown, trend, date with age, and associated price. The parameters are fully covered, behavior is explained, and no critical calling information is missing.

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 the baseline is 3. The description adds value by enumerating accepted asset values (BTC, ETH, SOL, XRP), reinforcing the default, and explicitly documenting the 'symbol' alias. This goes beyond the schema's minimal descriptions.

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 precisely identifies the resource (spot-ETF net flows in USD), the supported assets (BTC, ETH, SOL, XRP with BTC default), and the output shape (latest day total, per-fund breakdown, trailing daily trend). This clearly distinguishes it from other flow-related siblings like flow_orderbook or flow_whale_context.

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?

The description clearly implies when to use it: whenever ETF flow data for a supported asset is needed. It provides important context about timing (flows settle behind spot, skip weekends) and interpretation (positive means net inflows), but does not explicitly name alternatives or state when not to use this tool.

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

A4/5.0
Disambiguation4/5

Tools are grouped by clear prefixes and mostly target distinct resources; market_quotes vs research_token_view, market_top_movers vs market_trending, and funding_current vs market_quotes have some field or purpose overlap, but descriptions draw enough scope boundaries for an agent to choose correctly in most cases. No two tools are truly interchangeable.

Naming Consistency5/5

All 30 tool names use lowercase snake_case with a consistent domain-prefix convention such as market_, flow_, research_, sentiment_, and catalysts_, making the surface predictable. Even helpers like utc_time and risk_position_size fit the same noun-oriented pattern without style mixing.

Tool Count2/5

At 30 tools this set crosses the 'too many' threshold, and several tools reproduce data already available through broader ones such as research_token_view and market_quotes. The breadth is defensible for a crypto-research platform, but the surface feels heavy and could be consolidated.

Completeness5/5

The tool set covers the read-only crypto research workflow thoroughly: market data, candles, derivatives, funding, OI, order book, whale flows, ETF flows, on-chain metrics, news, sentiment, prediction odds, technicals, regime/positioning scans, and position sizing. It also includes health and UTC helpers that close practical workflow gaps, with no obvious dead ends.

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