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Python
Remote

convert_timezone

Convert datetime between timezones using IANA names, with DST-aware adjustments. Get the converted local time, UTC offset, and DST status.

Instructions

Convert a datetime from one timezone to another (DST-aware).

Uses Python's built-in IANA timezone database. No external API needed.

Args: datetime: ISO 8601 datetime string (e.g. "2024-06-15T14:30:00") from_tz: IANA source timezone (e.g. "America/New_York", "UTC") to_tz: IANA target timezone (e.g. "Asia/Tokyo", "Europe/Berlin")

Returns: dict with keys: result, result_date, result_time, utc_offset, is_dst, cost_usd

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
to_tzYes
from_tzYes
datetimeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses DST awareness, IANA database usage, no external API, and output keys including cost_usd. However, it does not explain cost_usd semantics, error cases, or side effects.

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?

Two-sentence summary followed by structured Args and Returns sections. No fluff, purpose is front-loaded, and every sentence contributes useful information.

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 tool with no output schema, the description lists output keys but not value types or semantics (notably cost_usd). It also lacks error-handling info, leaving gaps for an agent to fully self-serve.

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

Parameters5/5

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

Schema coverage is 0%, so the description fully compensates. It provides format and examples for datetime, and IANA timezone examples for from_tz/to_tz, adding meaning far beyond the plain string type in 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?

Clear verb 'convert' with a specific resource 'datetime from one timezone to another', plus DST-aware adds specificity. It distinguishes itself from sibling converters like convert_currency and convert_units.

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

Usage Guidelines2/5

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

No explicit when-to-use, exclusions, or alternative routing. The description implies usage through its purpose, but among many sibling converters it offers no selection 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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