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.

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.

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.

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.

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.

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.