Scatter a number of dates across a span, for generating events. The seed is required and the draw is fully deterministic: the same calendar, span, count, seed and unique flag always give the same dates, on any machine. unique=true (default) draws without repeats and fails if count exceeds the number of days in the span. Results come back sorted.
| Name | Required | Description | Default |
|---|---|---|---|
| end | Yes | ||
| seed | Yes | ||
| count | Yes | ||
| start | Yes | ||
| unique | No | ||
| calendar | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 well: it discloses determinism across machines, the required seed, repeat/unique behavior, the failure condition when count exceeds available days, and that results are sorted. This is substantial behavioral context beyond the bare schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences deliver the core purpose, determinism guarantee, uniqueness semantics, failure mode, and sort order. Every sentence earns its place, and the most important behavioral constraints are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has six parameters, three nested open objects, no output schema, and no annotations. The description explains determinism, uniqueness, failure, and sorted results, but it omits how 'calendar', 'start', and 'end' should be represented or constructed, and it does not describe the format of the returned dates beyond being sorted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 for undocumented parameters. It adds useful meaning for 'seed' (required, deterministic) and 'unique' (default true, no repeats, failure condition), but it does not clarify the structure or semantics of 'calendar', 'start', and 'end', which are open objects with no schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('scatter'), a clear resource ('a number of dates across a span'), and an intended use ('for generating events'). It is clear about what the tool does, though it does not explicitly name or contrast sibling tools, so it stops short of full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for generating events' provides a clear contextual trigger for when to use this tool. It does not explicitly state when not to use it or point to alternatives, but the intended use case is unambiguous enough for selection among the listed date-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct date/calendar operation: arithmetic, conversion, weekday lookup, period membership, moon phase, daylight, event queries, formatting/parsing, and two different rendering outputs. Even superficially similar tools (calendar_weekday vs nth_weekday_of_month, calendar_events vs calendar_periods) ask clearly different questions that the descriptions make unambiguous.
Names are all lowercase snake_case and mostly follow a verb_first or noun_query pattern, but there is a mix: add_to_date, convert_date, and parse_calendar_date are imperative, while moon_phases, sun_daylight, and calendar_events are noun phrases describing what they return. The calendar_ prefix on three tools and consistent rendering parse/format pairs help readability, so this is a minor deviation, not chaos.
15 tools sits at the upper bound of the ideal range for a focused domain toolkit. Every tool addresses a genuine calendar use case (define, convert, query, render, validate, generate), and none feels redundant or extraneous.
The set covers the full lifecycle of working with a custom calendar: validation before use, conversion between representations, date arithmetic and intervals, weekday and period queries, recurring events and daylight/moon data, formatting/parsing, and visual rendering. No obvious dead ends or missing operations come to mind for the stated domain.