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srs

Retrieve sunrise and sunset times for Hong Kong by year, month, and day. Returns data in JSON or CSV format.

Instructions

Times of Sunrise/Sunset (SRS) API Request

Parameters:

  • year: 2018-2024

  • month: (Optional) 1-12 (requires year)

  • day: (Optional) 1-31 (requires year and month)

  • rformat: 'json' or 'csv' (Response format, default: csv)

Request Example: https://data.weather.gov.hk/weatherAPI/opendata/opendata.php?dataType=SRS&year=2025&month=1&rformat=json

Response Keys (JSON format):

  • type: Array with data type ["Sunrise/Sunset Times"]

  • fields: Array with field names ["Year", "Month", "Day", "Sunrise", "Sunset"]

  • data: Array of arrays with sunrise/sunset data

  • legend: Array with information

Response Keys (CSV format):

  • Type: Data type line

  • Header row: Year,Month,Day,Sunrise,Sunset

  • Data rows: Actual sunrise/sunset data

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesYear between 2018-2024
monthNoOptional month (1-12) when specific month data is needed
dayNoOptional day (1-31) when specific day data is needed
rformatNoOutput format: 'json' or 'csv' (default: 'csv')csv
Behavior4/5

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

With no annotations provided, the description carries the full burden. It details the response formats (JSON/CSV), fields, and provides an example URL. However, it does not mention rate limits or error handling.

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

Conciseness2/5

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

The description is verbose, including an example and full response keys for both formats. It could be more concise by omitting redundant parameter details and focusing on key behavioral information.

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?

Given no output schema, the description adequately covers the response structure. It explains both JSON and CSV formats. However, it lacks context on limitations (e.g., historical data only) and error conditions.

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 coverage is 100%, so the description adds minimal new meaning. It repeats parameter ranges and defaults that are already in the schema. No additional semantics beyond the schema.

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 'Times of Sunrise/Sunset (SRS) API Request', specifying the verb (request) and resource (sunrise/sunset times). It distinguishes from sibling tools by focusing on this specific phenomenon.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives. Usage is implied through the purpose, but no when-not-to-use or alternative guidance is provided.

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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