cryptoetf

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

The annotations already declare readOnlyHint=true, and the description adds meaningful behavioral context: it returns a daily time series, uses net USD millions, and defines sign semantics (positive = inflow, negative = outflow). No pagination or missing-data behavior is described, but for a simple read-only tool this is sufficient.

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 two sentences with no wasted words. It front-loads the core action and resource, then immediately clarifies the return format and sign convention. Every sentence contributes useful information.

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?

With one well-specified parameter and a read-only annotation, the description is complete for selecting and invoking the tool correctly. It explains the data range, unit of measurement, and interpretation of positive/negative values, which is especially important because there is no output schema.

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 description coverage is 100%, so the single 'asset' parameter is fully documented by the schema's enum and description. The tool description only reinforces that it targets one crypto asset, adding little beyond the schema; the baseline of 3 is appropriate.

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 uses a specific verb ('Get'), names a concrete resource ('daily net ETF flow history for a single crypto asset'), and adds temporal scope ('over the last 30 days'). This clearly distinguishes it from sibling tools like get_prices or 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 description makes the use case clear: fetch daily ETF flow history for one asset over a 30-day window. It does not explicitly name alternatives or exclusion conditions, but the single-asset scoping and ETF-specific language provide strong contextual guidance against using it for multi-asset summaries or price data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds useful interpretive behavior beyond annotations: baseline 100, above meaning bullish net inflow bias, below meaning bearish outflow bias.

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 tight sentences with no filler: the first identifies the operation and scope, the second explains the score interpretation. Everything present earns its place.

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 zero-parameter read-only tool, the description fully covers what the score means, the baseline, and the bullish/bearish interpretation. No output schema exists, but the description gives enough context for an agent to understand and use the returned sentiment value.

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, so the baseline score is 4. There is no parameter information needed, and the description adds no unnecessary parameter guidance.

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?

States a specific verb and resource: 'Get the composite CEFI sentiment score across all tracked assets.' This clearly distinguishes it from siblings like get_asset_flows or get_prices, which focus on per-asset or pricing data.

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 use as a top-level composite market sentiment read rather than per-asset flows or analytics. It does not explicitly name alternatives or exclusions, but the scope phrasing makes the intended use reasonably clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already set readOnlyHint=true and openWorldHint=false, but the description adds significant behavioral context: the one-business-day publication lag, clarification that referenceIsToday is normally false, the meaning of referenceDate, and the note about Mondays. It also explains that totalUsdM is pre-summed. These details go well beyond annotations and prevent misinterpretation of stale data.

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 paragraph of six sentences, each carrying essential information: scope, examples, sign convention, usage hint, the publication lag caveat, and the summation note. It is efficiently front-loaded and not overly verbose, though it could be tightened into bullet points. Still very readable and purposeful.

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 no-input tool, the description fully covers what an agent needs: what it returns, how to interpret the numbers, potential staleness (with day-of-week clarification), and how the fields relate. The output schema is absent, so the description carries complete responsibility, and it does so thoroughly. No gaps remain.

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 input parameters, so the description has nothing to add about parameter meaning beyond the schema, which is trivially complete. The baseline for zero parameters is 4, and the description appropriately emphasizes output semantics instead. No information is missing.

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 ('Get'), a specific resource ('latest-day net ETF inflow/outflow in USD millions'), and a clear scope ('for every tracked crypto asset'), listing all assets. It also clarifies positive/negative semantics, so an agent can understand exactly what the tool returns. While it doesn't name sibling tools, the scope is so explicit that confusion is unlikely.

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 includes a clear usage context: 'Use this for a quick dashboard snapshot.' However, it does not mention alternatives (like get_asset_flows for detailed per-asset data) or exclusions when not to use it. Since it provides a clear purpose but no explicit when-not, it falls short of the highest bar but is close.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already provide readOnlyHint=true and openWorldHint=false, and the description adds meaningful behavior: prices are sourced from major exchanges, refreshed frequently, and returned for all 13 assets. This is sufficient for a simple read-only snapshot and does not contradict any annotation.

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 tight sentences front-load the result content and scoping information. The enumerated asset list is necessary to define the fixed universe, and there is no filler or redundant wording.

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 no-input, read-only tool with no output schema, the description covers the key semantics: the exact data fields, the USD denomination, the fixed 13-asset universe, and freshness expectations. 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?

This tool has zero parameters, so the schema already fully covers the input surface. The description consequently needs no parameter elaboration, and the baseline 4 for a no-parameter tool is appropriate.

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 uses a precise verb-resource pair ('Get current spot prices... and 24-hour percentage change') and explicitly scopes the result to all 13 tracked assets by listing them. This makes it clearly distinguishable from sibling tools focused on flows, index, and analytics.

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 does not name sibling alternatives, but the content ('spot prices', '24-hour percentage change') makes the appropriate use case unmistakable against the flow/analytics siblings. No exclusions are stated, but for a zero-parameter read-only tool the context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.