Almanack

parse_calendar_date

Read a written date back into a date. Strict, with no fuzzy matching of any kind: literal characters must match character for character, month, weekday, era and period names must be names this calendar actually defines, and a weekday or period written into the string must be one that date really falls on. A string that does not fit is an error naming what did not fit; it never returns a best guess. Use the same pattern that wrote the string. A pattern that wrote a time of day gives the time back too.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes
`pattern`	Yes
`calendar`	Yes

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It thoroughly explains strict character-by-character matching, calendar-defined name restrictions, weekday/period consistency checks, error behavior that names what did not fit, and the absence of fuzzy guessing.

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?

The description is dense but every sentence earns its place: purpose, strict mode, error behavior, pattern reuse, and time handling are all covered without redundancy. It is front-loaded with the core action and then layers constraints and usage guidance.

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?

For a no-output-schema tool with three parameters and a nested calendar object, the description covers the essential behavior, inputs, and error outcomes well. It leaves some details implicit, such as exact pattern syntax and calendar-object structure, but these appear to be shared context with formatting tools. Overall it is sufficient for selection and mostly sufficient for correct invocation.

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 description coverage is 0%, so the description must add meaning beyond the input schema. It does: text is the written date, pattern is the pattern that created the string, and calendar provides the defined names. It does not provide concrete examples of pattern syntax, but it compensates reasonably for the missing schema documentation.

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 states a specific verb and resource: it 'Read[s] a written date back into a date' and clarifies it is the inverse of formatting. The strictness and pattern-reuse language distinguish it from siblings like convert_date and format_calendar_date without needing to open their schemas.

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 usage context: use the same pattern that wrote the string, and a time-of-day pattern yields the time back. It does not explicitly spell out when not to use this tool versus alternatives, but the inverse relationship to formatting is strongly implied.

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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