get_weekly_analyticsGet 7-day aggregated ETF flow analytics for all tracked assets. Returns total net flow, average daily flow, and count of positive vs negative days per asset. Useful for a quick momentum read without pulling the full time series.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so no safety contradiction exists. The description adds useful behavioral detail by specifying the 7-day aggregation window, the exact returned metrics (total net flow, average daily flow, positive/negative day counts), and the 'all tracked assets' scope, which is valuable since there is no output schema.
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?
Two sentences deliver the core action, the return contents, and the intended use case with no filler. The most important facts are front-loaded, and the final sentence earns its place by helping the agent decide when to invoke the tool.
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?
For a parameterless read-only tool, the description covers what it does, what it returns, its scope, and when it is useful. There is no output schema, but the description compensates by naming the output fields. Nothing essential is missing for correct invocation.
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 an empty input schema, so there is nothing for the description to explain beyond confirming no inputs are required. The baseline for a no-parameter tool is 4, and the description does not introduce any misleading parameter information.
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 states a specific verb and resource: 'Get 7-day aggregated ETF flow analytics for all tracked assets.' It also clarifies the output fields and contrasts with 'pulling the full time series,' distinguishing it from sibling tools like get_asset_flows and get_flows_summary.
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 phrase 'Useful for a quick momentum read without pulling the full time series' gives clear usage context and implies it is the lighter-weight alternative to more detailed flow tools. It does not explicitly name siblings or state when not to use it, so it stops short of a 5.
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 has a clear primary focus: single-asset historical flows, composite sentiment index, latest cross-sectional flows, prices, and weekly aggregation. The only minor overlap is between get_flows_summary and get_weekly_analytics, but their descriptions make the distinction obvious.
All tool names follow a consistent get_<noun> pattern using snake_case, with clear descriptive suffixes like asset_flows, flows_summary, and weekly_analytics. There is no mixing of conventions or vague verbs.
Five tools is well-scoped for a read-only crypto ETF analytics server. Each tool covers a distinct data need without redundancy, and the count is appropriate for the narrow domain.
The set covers the core query surface for ETF flow data: recent daily snapshot, single-asset history, weekly aggregates, sentiment index, and prices. Minor gaps exist, such as no multi-asset historical comparison or explicit asset list endpoint, but these are unlikely to cause major agent failures.