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weather_log

Archive hourly weather data for the past 24 hours into a local log for training review. As official data expires after 24 hours, run daily to preserve climate context before morning runs or any workout analysis.

Instructions

把过去 24 小时逐小时实况归档到本地气象日志,供日后回溯训练当时的气候。 官方只保留 24 小时,因此建议每天至少调用一次(尤其在复盘晨跑之前)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo成都

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It mentions the tool archives to a local log and notes that the official source retains only 24 hours, implying data might be lost if not called daily. However, it does not reveal whether the operation is irreversible, if previous logs are overwritten, or what authentication is required. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise at two sentences, front-loading the main action (archive weather data) and then providing a usage recommendation. Every sentence adds value, with no fluff. Slight dock for not being perfectly structured (no line breaks or section headers), but it is efficient.

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

Completeness3/5

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

Given the tool is simple (1 param, no required params, has an output schema), the description is mostly adequate: it explains what, why, and when. However, the lack of parameter documentation and no behavioral details on what happens to old data (append vs. overwrite) or the return format (output schema exists but is not described) leaves some gaps. With a richer output schema, description needn't explain return values, but it's still incomplete for a logging operation.

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 0%, so the description should compensate. The description does not mention the 'city' parameter at all, missing an opportunity to clarify its meaning beyond the schema. Baseline with 0% coverage and zero parameter mention is 2, but the schema provides a default value and title, partially informing the agent, so this is borderline. The tool only has one parameter, so the lack of semantic help is a moderate gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool archives hourly weather data from the past 24 hours into a local log for future training review. It distinguishes itself from sibling weather tools like weather_now and weather_forecast by focusing on archival and long-term climate review.

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 explicitly recommends calling the tool at least once daily, especially before reviewing a morning run, which gives clear usage context. It does not, however, directly contrast with alternatives like weather_at or weather_forecast, but the recommendation implies when to use it versus those.

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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