Score a specific river cruise: the chance a sailing departing on a given date meets low water (high water on the Seine) at its river's tightest stretch. Uses the live daily forecast where it reaches (~7 months) and the thirty-year weekly record beyond, plus what the same dates actually did in each of the last five years.
| Name | Required | Description | Default |
|---|---|---|---|
| river | Yes | ||
| nights | No | ||
| departure_date | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides meaningful methodology: it uses the live forecast to ~7 months, the 30-year weekly record beyond that, and actual same-date outcomes from the last five years. It also highlights the Seine's high-water inversion, adding useful context beyond the 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, front-loaded with the core purpose and followed by a compact explanation of data sources. No filler or redundancy.
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?
The description is largely complete for a medium-complexity scoring tool with no output schema: it explains the purpose, the special Seine case, data horizons, and historical anchoring. Minor omissions are the 'nights' parameter and explicit output scale, but these do not undermine overall usability.
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 description adds meaning for river and departure_date via 'sailing departing on a given date' and 'river's tightest stretch,' but does not mention the optional 'nights' parameter. With 0% schema description coverage, leaving one of three inputs unexplained is a notable gap.
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 clearly states what the tool does: it scores a specific river cruise by estimating the chance of low water (or high water on the Seine) at a given date and river's tightest stretch. This distinguishes it from siblings like get_live_gauges and get_monthly_odds.
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 frames the tool as being for a specific sailing with a given departure date, establishing clear context for when to use it. It does not explicitly name alternative tools or state when not to use it, stopping 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 targets a distinct need: live readings, month explanations, 12-month odds, and specific cruise scoring. No two tools overlap in purpose.
Three tools follow get_ convention, but score_sailing uses a different verb. Minor deviation does not affect clarity.
Four tools cover the domain without redundancy or bloat. Each serves a clear role in assessing river cruise risk.
The set covers current conditions, month-level explanation, forward-looking odds, and cruise-specific scoring. Minor gaps like historical raw data or river metadata exist but don't undermine core workflows.
