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hub_sunrise

Read-only

Sunrise, sunset, and day length for one coordinate from sunrise-sunset.org. Their current docs require a visible attribution and do not require a key. Does not spend points and does not accept a URL. If you supply fields, the hub returns privacy_consent_required until the controller has accepted the current privacy version. Do not invent that acceptance.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lat": "<lat>",
      "lon": "<lon>"
    },
    "name": "hub_sunrise"
  }
}

Input Schema

NameRequiredDescriptionDefault
latYes
lonYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.3/5.0
Behavior4/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses several non-obvious behaviors: no API key needed, a visible attribution requirement, no point cost, and a specific error state (privacy_consent_required) with a warning not to fake acceptance. The one weak spot is 'if you supply fields', which is undefined terminology that does not map to anything in this schema.

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

Conciseness3/5

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

The purpose is front-loaded in the first sentence and the cost/attribution notes are useful. However, the 'supply fields' sentence is opaque and, given additionalProperties: false, reads as boilerplate that does not apply to this tool, which costs clarity.

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?

For a simple two-parameter read tool with safety annotations, most of what an agent needs is present. The notable gaps are coordinate format expectations and any indication of the return shape (sunrise, sunset, day_length, timezone), which matters because there is no output schema to fall back on.

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

Parameters2/5

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

Schema description coverage is 0% for two required parameters, so the description must carry the burden and it largely does not. It says 'one coordinate' but never specifies decimal degrees, WGS84, valid ranges, or which coordinate is which beyond the parameter names lat and lon.

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 first sentence names a specific resource and scope: sunrise, sunset, and day length for one coordinate, sourced from sunrise-sunset.org. An agent can distinguish this from hub_geocode or hub_weather-point without opening the schema, although it never explicitly says the tool returns values rather than just describing them.

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 phrase 'does not accept a URL' and 'for one coordinate' imply that URL or place-name inputs belong to a sibling (likely hub_geocode), but that alternative is never named. There is also no explicit when-to-use or when-not-to-use statement, so routing to the right hub tool is left to inference.

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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