API Acre

data.timezone-convert

Read-onlyIdempotent

Convert an offset-aware ISO 8601 instant or a local wall time between IANA time zones with explicit DST gap and repeated-hour handling, nearby transition evidence, and a pinned local time-zone database.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`timestamp`	Yes	ISO 8601 timestamp. Include Z or an offset for an exact instant, or provide a naive local timestamp together with source_timezone.
`ambiguous_time`	No	How to resolve a repeated local wall time during a backward DST transition; nonexistent spring-forward times are always rejected	reject
`source_timezone`	No	Required for a timestamp without an offset; optional source display zone for an offset-aware timestamp
`target_timezone`	Yes	Target IANA time-zone name, for example Europe/London
`include_transitions`	No	Include previous and next offset transitions within 370 days

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes	Structured IANA timezone conversion result
`meta`	Yes
`service`	Yes
`version`	Yes
`request_id`	Yes	Unique request identifier

TDQS

A3.9/5.0

Behavior4/5

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

The description adds significant behavioral context beyond the annotations: explicit handling of DST gaps and repeated hours, provision of nearby transition evidence, and use of a pinned local time-zone database. Annotations (readOnlyHint, idempotentHint) are consistent, and no contradictions exist.

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 a single sentence that densely packs key features. It is front-loaded with the core action 'Convert... between IANA time zones'. While effective, it could be slightly more readable if split into two sentences, but remains concise.

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 the tool's complexity (5 params, output schema present), the description covers core functionality, special DST handling, and database source. With an output schema, return values need not be explained. A small gap: no mention of required input format constraints beyond schema examples, but overall sufficient.

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 100%, so the baseline is 3. The tool description does not add extra parameter-level semantics beyond what the schema already provides (clear descriptions for all 5 parameters).

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 identifies the tool's function: converting timestamps between IANA time zones, with specific details about handling DST gaps and repeated hours. It distinguishes itself from generic conversion tools like data.convert, and is unique among siblings.

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 implies usage for timezone conversion but does not explicitly state when to use this tool versus alternatives (e.g., data.convert). No exclusions or when-not-to-use 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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TDQS

A3.8/5.0

Disambiguation4/5

Tools are grouped into clear domain prefixes (crypto, data, developer, document, research, web) and each tool name describes a specific function; however, a few umbrella tools like web.full-audit and data.contract overlap with their more targeted counterparts, creating minor ambiguity.

Naming Consistency5/5

All tool names follow a consistent pattern: a domain prefix, a dot, and a hyphenated lowercase compound name (e.g., crypto.base-block-inspect, web.seo-audit). This makes naming predictable and easy to scan.

Tool Count1/5

At 63 tools, the surface area is very large and exceeds the 50+ threshold for extreme mismatch. While the tools are organized into six domains, the sheer number makes it difficult for an agent to select efficiently, and some tools are bundled combinations of others.

Completeness5/5

Each domain offers a thorough set of operations: crypto covers address, account, block, contract, events, gas, and transaction inspection; data covers cleaning, conversion, schema, and validation; developer covers code review, dependency/license audits, and test generation; research covers SEC, OFAC, GLEIF, and USAspending; web covers extraction, SEO, security, and performance. No obvious dead ends exist for the read-only/inspection purpose.

Resources

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