Calcgrid

IANA Time Zone Transition List

list_time_zone_transitions

Read-onlyIdempotent

Use this when you need the next or historical daylight-saving/offset changes for scheduling, payroll, travel, audits or a regression test, with a specific reproducible tzdb version. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery.

Do not use this when you only need to convert one ordinary date-time, need legal advice about a jurisdiction's time law, or need changes announced after this pinned release. What it computes: Lists every UTC-offset transition for one IANA zone and date range using pinned tzdb 2026d, including the local boundaries, offsets, abbreviations and whether the clock creates a gap or overlap. Example user requests: List every 2026 UTC-offset transition in America/New_York with local boundaries. | When does Australia/Adelaide change clocks between 2026-01-01 and 2027-01-01? | 列出 Europe/London 在 2026 年的夏令时转换点、前后偏移和 IANA 数据版本。 Inputs: time_zone (string); start_date (date); end_date (date). Complete JSON argument examples: {"time_zone":"America/New_York","start_date":"2026-01-01","end_date":"2026-12-31"} Outputs: time_zone, resolved_zone_id, start_date, end_date, transition_count, transitions, tzdb_version, dataset_version, source_url, source_sha256, coverage_note. Formula: select zone transition instants whose local boundary before or after lies inside [start_date, end_date] Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/time-zone-transitions with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/time/time-zone-transitions.md

Input Schema

TableJSON Schema

Name	Required	Description
`end_date`	Yes	Last local calendar date to inspect; ranges may not exceed 3,660 days.
`time_zone`	Yes	IANA zone identifier present in tzdb 2026d.
`start_date`	Yes	First local calendar date to inspect (1900-01-01 through 2100-12-31).

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.

Changed3 schema fields changedSep 27, 2026

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: +[
+  {
+    "end_date": "2026-12-31",
+    "start_date": "2026-01-01",
+    "time_zone": "America/New_York"
+  }
+]

AddedSep 26, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Even with readOnly/idempotent/non-destructive annotations, the description adds substantial behavior: pinned tzdb 2026d, inclusion of local boundaries, offsets, abbreviations, gap/overlap flags, and the exact selection formula. The REST fallback and coverage note further clarify what the agent can rely on. No contradiction with annotations.

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 with purpose, exclusions, computed behavior, example requests, inputs, outputs, formula, and fallback. It is front-loaded with the key use case and negative conditions, though the Inputs/example sections partly duplicate the schema and could be tighter.

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?

Given the tool's moderate complexity, the 100%-covered schema, rich annotations, and presence of an output schema, the description is complete: it covers selection rationale, output fields, version pinning, request examples, and a fallback endpoint. An agent has everything needed to invoke it correctly and interpret results.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents the three parameters, formats, and range limits. The description adds clarifying semantics in the formula (transitions whose local boundary before or after lies inside the date range), which affects how start_date and end_date should be interpreted. The example JSON mirrors the schema but is still a useful concrete reference.

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 opens with a specific verb and resource: 'Lists every UTC-offset transition for one IANA zone and date range,' and differentiates it from single-date conversion by explicitly excluding that case. The scope (next/historical DST changes, pinned tzdb version) makes the tool's role unmistakable among siblings like convert_time_zone and resolve_local_time.

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?

It gives explicit when-to-use scenarios (scheduling, payroll, travel, audits, regression tests requiring a reproducible tzdb) and explicit when-not-to-use scenarios (simple conversions, legal time-law questions, post-release changes). Although it doesn't name convert_time_zone, the 'ordinary date-time conversion' exclusion clearly routes the agent away from the nearest sibling.

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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