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DeriveAI x402 APIs

by io.github.deriveit33z-ship-it
OverviewDiscussionsAdmin

prayer_times

Islamic prayer times for any city worldwide: Fajr, Dhuhr, Asr, Maghrib, Isha. Includes sunrise, Hijri date, and multiple calculation methods (Umm Al-Qura, ISNA, MWL).

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": {
      "city": "<city>"
    },
    "name": "prayer_times"
  }
}

Input Schema

NameRequiredDescriptionDefault
cityYesCity name (e.g., Dubai, London, Jakarta)
dateNoDate in DD-MM-YYYY format (optional, defaults to today)
countryNoCountry name (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It mentions supported calculation methods and output contents (sunrise, Hijri date), but does not disclose error handling, rate limits, or behavior for invalid inputs (e.g., unknown city, invalid date). The description gives a reasonable overview but lacks depth.

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 a single, well-structured sentence that immediately conveys the core purpose and key outputs. It is concise, front-loaded, and contains no redundant information, earning a top score.

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?

The tool is relatively simple with 3 parameters and no output schema. The description covers the main response elements (prayer times, sunrise, Hijri date, calculation methods) and the global scope. It could add details about the response format, but the absence is not critical given the straightforward nature of the tool.

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?

The input schema has 100% coverage with descriptions for all three parameters, so the description itself adds little semantic value beyond what is already in the schema. It mentions 'any city worldwide' and calculation methods, but these do not clarify parameter usage further. Baseline 3 is appropriate given the schema's completeness.

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 the tool's function: providing Islamic prayer times for any city worldwide, listing the five daily prayers and additional details like sunrise and Hijri date. This distinguishes it from all sibling tools, which cover unrelated domains (e.g., weather, gold price, translation).

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?

While the description implicitly indicates when to use this tool (for prayer times), it does not provide explicit guidance on when not to use it or mention alternative tools. Given that this tool is unique among its siblings, the lack of direct alternatives is acceptable, but a clearer 'use this for prayer times' or note on constraints (e.g., city ambiguity) would improve guidance.

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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