Moltline TimeOps

Sla Due

sla_due

Read-onlyIdempotent

Compute when a ticket's SLA falls due, wall-clock or business-hours. PREMIUM (license).

Typical input {"opened_at": "2026-03-02T15:30", "sla_hours": 8, "business_hours_only": true} returns {"due": "2026-03-03T15:30", "mode": "business hours 09:00-17:00"}; with business_hours_only false the mode is "wall-clock".

Use when a response or resolution clock has started and one due moment is needed. Not for multi-step project schedules (deadline_planner). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "opened_at must be ISO YYYY-MM-DDTHH:MM"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`day_end`	No	Business day end, 24h HH:MM; must be later than day_start. Default "17:00".	17:00
`holidays`	No	Optional list of ISO YYYY-MM-DD dates that never count as working days.
`day_start`	No	Business day start, 24h HH:MM. Default "09:00".	09:00
`opened_at`	Yes	When the SLA clock started, ISO datetime YYYY-MM-DDTHH:MM.
`sla_hours`	Yes	SLA length in hours; greater than 0, at most 24000; fractions allowed, e.g. 7.5.
`business_hours_only`	No	If true, only time inside day_start-day_end on business days counts toward the SLA.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint), the description adds critical error behavior: 'never raises a protocol error — it returns {"error": "..."}' and clarifies that every call is read-only and idempotent, making retry safe. This is substantial behavioral context not present in annotations.

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 serves a purpose: purpose, example, usage guidelines, error handling, idempotency. The description is concise (~100 words), front-loaded, and well-structured. No wasted words.

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?

Given the tool's 6 parameters, output schema existence, and sibling tools, the description covers all critical aspects: what it computes, when to use it, error behavior, retry safety, and a concrete example. An AI agent has all necessary information to select and invoke the tool correctly.

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 100% with detailed parameter descriptions. The description adds value by showing a typical input example and explaining how 'business_hours_only' affects the output mode, which is not in the schema. While schema is already strong, the example and relationship clarification merit a slight boost above baseline.

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 clearly states the tool computes SLA due times for tickets, using either wall-clock or business hours. It immediately distinguishes itself from the sibling 'deadline_planner' by noting it is not for multi-step project schedules.

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

Usage Guidelines5/5

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

Explicit guidance: 'Use when a response or resolution clock has started and one due moment is needed. Not for multi-step project schedules (deadline_planner).' It also explains error handling and retry safety, leaving no ambiguity about when to choose this tool.

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

A4.7/5.0

Disambiguation4/5

Each tool targets a distinct time-related operation: business day math, backward scheduling, timezone overlap, recurrence rules, and SLA due times. The descriptions include 'Use when ... Not for ...' sections that clearly differentiate them, though business_days and deadline_planner both involve business days and could be confused for near-simple tasks.

Naming Consistency5/5

All tool names use a consistent snake_case pattern with clear, descriptive verb+noun or noun_verb combinations (business_days, deadline_planner, meeting_overlap, recurrence_expand, sla_due). The naming is predictable and intuitive for the domain.

Tool Count5/5

Five tools is a well-scoped set for a time operations server, covering core scheduling needs without being too few or too many. Each tool addresses a distinct use case and the count is appropriate for the server's purpose.

Completeness4/5

The tool set covers major temporal operations: date arithmetic, backward planning, timezone coordination, recurrence, and SLA tracking. A minor gap is the lack of a plain calendar-day difference tool (as noted in business_days description), but the core domain is well covered and agents can work around this gap.

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