Almanack

calendar_periods

Which named periods of the year a date falls in — a season, a tide, a term. Answers with a list, not one: a calendar may declare several cycles of periods and a date sits in one of each, so seasons and festival tides come back together. Each answer says which day of the period it is and how long the period runs, which is how 'early autumn' becomes a comparison rather than a guess. An empty list is a legal answer and means the calendar's periods do not cover that day; validate_calendar_spec reports the gaps and overlaps in a whole cycle. Pass 'dates' for more than one. Answers up to 1000 in one call, in the order given, as {count, ok, results}. Prefer this over one call per item: the spec travels once instead of once each.

Input Schema

TableJSON Schema

Name	Required	Default
`date`	No
`dates`	No
`calendar`	Yes
`on_error`	No	fail

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations, the description carries the burden, and it discloses many behavioral traits: multi-cycle returns, empty-list semantics, ordering, a batching limit of 1000, and the {count, o, results} response shape. It does not cover error/on_error behavior, but otherwise is unusually transparent.

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 dense and front-loaded, with each sentence contributing either behavioral semantics or a usage tip. A couple of stylistic phrases (''early autumn' becomes a comparison rather than a guess') add color but are not essential.

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?

Because there is no output schema, the description appropriately explains the return shape and item contents. However, the lack of coverage for the required 'calendar' parameter and the error/on_error behavior means the definition is not fully sufficient on its own.

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

Parameters2/5

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

Schema description coverage is 0%, and the description only directly addresses the 'dates' parameter ('Pass 'dates' for more than one') and implicitly mentions the calendar spec. The required 'calendar' parameter and 'on_error' parameter are not sufficiently explained, leaving real gaps for a low-coverage 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?

The description immediately states the operation: identifies which named periods of the year a date falls in — seasons, tides, terms. It also distinguishes itself from likely siblings by emphasizing it returns a list rather than a single value and handles multiple period cycles.

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

Usage Guidelines4/5

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

The description gives clear batching guidance ('Prefer this over one call per item') and points to validate_calendar_spec for gap/overlap analysis. It does not explicitly exclude other sibling tools, but the domain is clear.

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

A3.9/5.0

Disambiguation4/5

Each tool targets a distinct calendar operation, and the descriptions carefully draw boundaries between related concepts. There is modest overlap: convert_date also reports a named period, and calendar_events can answer nth-weekday questions that overlap with nth_weekday_of_month, so an agent might occasionally pick the wrong entry point.

Naming Consistency3/5

All names are readable and consistently snake_case, but the set mixes verb-led names like convert_date and render_timeline with noun-led names like calendar_events and moon_phases, plus one prepositional verb in add_to_date. This is a readable mixture rather than a uniform verb_noun pattern.

Tool Count5/5

Fifteen tools sits at the upper end of the typical well-scoped range, but every tool fills a distinct role for an almanac-style server: date math, conversion, calendar queries, formatting, parsing, rendering, lunar and solar calculations, generation, and validation. The batched plural parameters also make the count feel intentional rather than bloated.

Completeness4/5

The surface covers the domain unusually well: conversion, arithmetic, events, periods, weekdays, format/parse, SVG rendering, moon phases, daylight, scattering, and validation all have dedicated tools. The main gap is introspection—there is no direct way to list a calendar spec's months, eras, week structure, periods, or formats beyond what other tools reveal through errors and outputs.

Resources

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