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arnfa_plan_day

Plan a weather-fit day in any area: get an ordered itinerary of real places based on the forecast at each arrival time, so you visit each spot in suitable conditions.

Instructions

Plan a weather-fit day in an area: the engine reranks real places by the forecast at each arrival time and returns an ordered itinerary. Real forecast only — never fabricated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dayNo0=today … 6 days ahead
areaYesarea key from arnfa_list_areas, e.g. 'chiang-mai'
budgetNominutes: 150=quick, 240=half day, 420=full day
Behavior5/5

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

With no annotations provided, the description fully carries the transparency burden. It discloses key behavioral traits: reranking based on forecast at arrival time, returning an ordered itinerary, and the strong guarantee that it uses 'real forecast only — never fabricated.' This goes beyond the schema and sets clear expectations, including a data integrity promise.

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?

The description is two short sentences, tightly packed with useful information: purpose, mechanism, output, and a key behavioral assurance. It is front-loaded with the main verb and avoids any filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a planning tool with no output schema, the description sufficiently explains the return value ('ordered itinerary') and the overall workflow. It could be more specific about the number of places returned or itinerary structure, but given the tool's scope and the completeness of the parameter schema, it is adequately complete for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with each parameter (area, day, budget) already explained clearly. The description itself adds no new parameter info beyond mentioning 'area' generically. Since the schema already does the heavy lifting, a baseline score of 3 is appropriate.

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 clearly states a specific verb ('Plan') and resource ('a weather-fit day in an area'), and explains the mechanism (reranks places by forecast) and output (ordered itinerary). It distinguishes itself from sibling tools like arnfa_list_areas (just lists areas) and arnfa_sky_now (current sky), making its purpose unambiguous.

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 this tool: when the user wants a day plan optimized for weather in a specific area. It does not explicitly mention alternatives or when not to use it, but the context is clear and the 'ordered itinerary' outcome signals it as the planning tool among siblings.

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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