Calcgrid

IANA Local Time Resolver

resolve_local_time

Read-onlyIdempotent

Use this when you must safely turn a named-zone local time into an instant, validate a scheduled time around a daylight-saving transition, or preserve every possible interpretation instead of silently choosing one. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery.

Do not use this when the input already includes a numeric UTC offset or Z, the task only needs the current clock time, or latitude/longitude must first be mapped to a zone. What it computes: Resolves a local wall-clock time with pinned IANA tzdb 2026d. Returns every valid UTC candidate for a repeated fall-back time, or the exact gap and shift-forward suggestion for a nonexistent spring-forward time. Example user requests: Resolve 2026-11-01 01:30 in America/New_York and return both UTC candidates. | Does 2026-03-08 02:30 exist in New York? Show the DST gap. | 判断 Australia/Adelaide 的 2026-10-04 02:30 是否存在，并给出时区数据版本。 Inputs: local_datetime (string); time_zone (string). Complete JSON argument examples: {"local_datetime":"2026-11-01T01:30:00","time_zone":"America/New_York"} | {"local_datetime":"2026-03-08T02:30:00","time_zone":"America/New_York"} Outputs: local_datetime, time_zone, resolved_zone_id, status, candidate_count, candidates, gap, related_transition, previous_transition, next_transition, tzdb_version, dataset_version, source_url, source_sha256, coverage_note. Formula: for each zone offset o: candidate_utc = local_wall_time + o; keep candidates whose active offset at candidate_utc equals o Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/local-time-resolver with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/time/local-time-resolver.md

Input Schema

TableJSON Schema

Name	Required	Description	Default
`time_zone`	Yes	IANA zone identifier present in tzdb 2026d.
`local_datetime`	Yes	Wall-clock date and time without Z or a numeric offset; it will be interpreted only in time_zone.

Output Schema

TableJSON Schema

Name	Required	Description
`links`	No
`result`	Yes
`request`	Yes
`sources`	No
`success`	Yes
`version`	No
`freshness`	No
`timestamp`	Yes
`next_actions`	No
`service_version`	Yes	Deployed Calcgrid implementation version used for the result.

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedSep 27, 2026

addedInput schema / properties / local_datetime / maxLength
```
Added value: +19
```

addedInput schema / properties / local_datetime / pattern

Added value: +"^\\d{4}-\\d{2}-\\d{2}[T ](?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d)?$"

addedInput schema / properties / time_zone / maxLength
```
Added value: +64
```

addedOutput schema / properties / service_version

Added value: +{
+  "description": "Deployed Calcgrid implementation version used for the result.",
+  "type": "string"
+}

changedOutput schema / required

Previous value: -[
-  "success",
-  "request",
-  "result",
-  "timestamp"
-]New value: +[
+  "success",
+  "service_version",
+  "request",
+  "result",
+  "timestamp"
+]

Changed1 schema field changedSep 26, 2026

addedInput schema / examples

Added value: +[
+  {
+    "local_datetime": "2026-11-01T01:30:00",
+    "time_zone": "America/New_York"
+  },
+  {
+    "local_datetime": "2026-03-08T02:30:00",
+    "time_zone": "America/New_York"
+  }
+]

AddedSep 26, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already mark read-only/idempotent, and the description goes beyond them by disclosing exact DST behavior: repeated fall-back times return all UTC candidates, nonexistent spring-forward times return the gap and shift suggestion. It also states the pinned tzdb version and even provides the candidate-selection formula, giving agents full visibility into calculation logic.

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 long but well-structured: purpose and usage are front-loaded, followed by computing behavior, examples, inputs, outputs, formula, and fallback. Some sections (output field list, REST fallback) go beyond minimal needs, but each adds practical value for an agent invoking the tool via REST, and nothing is redundant enough to hurt clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool dealing with DST ambiguity, the description covers every important facet: it explains repeated/nonexistent times, gives multilingual examples, discloses the tzdb pin, lists output fields, and includes a REST fallback. Since an output schema exists, there is no need to describe return formats further, making the definition complete.

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 descriptions already fully document both parameters with patterns, maxLength, and the explicit 'no Z or numeric offset' rule for local_datetime. The description's 'Inputs: local_datetime (string); time_zone (string)' adds no new meaning, and examples duplicate the schema's examples, so the baseline 3 applies.

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 resolves a named-zone local wall-clock time into UTC candidates, explicitly handles DST gaps/repeats, and contrasts with siblings. The 'Use this when' and 'Do not use when' sections distinguish it from convert_time_zone and other date tools, leaving no ambiguity about its purpose.

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

Usage Guidelines5/5

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

Explicit 'Use this when' and 'Do not use when' conditions give unambiguous when-to-use guidance and exclusions. It also instructs the agent to call this tool directly rather than compute from memory or stop at discovery, reinforcing the tool's role as the authoritative resolver.

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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