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Perform batch date operations including diff, add, parse, format, and business days calculations. Get accurate results for date math without manual guessing.

Instructions

Batch date ops: [{"op": NAME, ...args}, ...] -> [result, ...]

diff(start, end, unit) until(target, unit, tz?) since(source, unit, tz?) -> float add(date, n, unit) -> ISO weekday(date) -> name business_days(start, end) -> int (Mon-Fri, end exclusive) parse(natural, tz?) -> ISO format(date, fmt) -> str

unit: seconds|minutes|hours|days|weeks (+ months|years for add).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations, so description carries burden. It discloses return format (array of results), mentions that business_days excludes end date, and shows unit options. However, it lacks detail on error handling, timezone effects for non-tz ops, and potential pitfalls of permissive input schema.

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?

Very concise, using compact DSL notation, no redundant sentences. However, the dense format may be hard to parse; slight improvement in structure (e.g., bulleted list) would help.

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?

Given the tool's complexity and low schema richness, the description covers all major operations but lacks details on return types for each op, error conditions, and full parameter semantics (e.g., format patterns). The presence of an output schema reduces burden, but the description still has gaps.

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 0%, but description compensates by detailing the ops structure, valid operation names, and their arguments (e.g., diff(start,end,unit)). This adds significant meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Batch date ops' and lists specific calculus (diff, add, etc.), clearly indicating it performs multiple date operations in a batch. It distinguishes from siblings like 'calc' (arithmetic) and 'now' (current time).

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

Usage Guidelines3/5

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

No explicit when-to-use or alternatives guidance. The DSL listing implies usage for date arithmetic, but no exclusions or comparisons to sibling tools are provided.

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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