Almanack

calendar_weekday

Which weekday a date falls on, as a 0-based index into the calendar's own week plus its name. Exact; never estimates. Returns weekday null when the date is an intercalary day the week does not count: those days sit outside the cycle and the week resumes after them exactly where it left off. Fails if the calendar defines no week rather than inventing a seven-day one. Pass 'dates' instead of 'date' 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

A4.5/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses exactness, the intercalary-day null return and week-resumption behavior, failure when the calendar defines no week, the 1000-item limit, ordering preservation, and the response envelope {count, ok, results}.

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?

Every sentence earns its place: purpose, edge-case behavior, failure mode, batching, limits, ordering, and output shape are all packed in without fluff. The description is front-loaded with the core meaning and only then adds behavioral details.

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 focused weekday-lookup tool with no annotations and no output schema, the description is unusually complete. It covers return value semantics, edge cases, error behavior, batch capacity, ordering, response shape, and a usage preference. No critical gap remains for an agent to invoke the tool correctly.

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 0%, so the description must compensate. It adds real meaning for date vs dates and the batch limit, and hints at calendar behavior by describing week definition failure. However, it leaves the calendar parameter's structure and the on_error parameter's semantics unexplained, so compensation is only partial.

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 what the tool does: determine which weekday a date falls on, returning a 0-based index and name. It adds precise behavioral distinctions such as exactness, intercalary-day null handling, and failure rather than inventing a week, making it clearly distinguishable from sibling date tools.

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 explicit batching guidance: pass dates instead of date for multiple items, and prefer a single batched call over one call per item. It does not explicitly name sibling alternatives or exclusion cases, but the intended usage context 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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