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Moltline TimeOps

by com.moltlinestudio

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
NameRequiredDescriptionDefault
day_endNoBusiness day end, 24h HH:MM; must be later than day_start. Default "17:00".17:00
holidaysNoOptional list of ISO YYYY-MM-DD dates that never count as working days.
day_startNoBusiness day start, 24h HH:MM. Default "09:00".09:00
opened_atYesWhen the SLA clock started, ISO datetime YYYY-MM-DDTHH:MM.
sla_hoursYesSLA length in hours; greater than 0, at most 24000; fractions allowed, e.g. 7.5.
business_hours_onlyNoIf true, only time inside day_start-day_end on business days counts toward the SLA.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint; the description reinforces these with 'Every call is read-only and idempotent' and adds critical behavioral details: error handling never raises protocol errors, returns structured error objects, and provides a concrete output example showing the 'due' and 'mode' fields, which is beyond the annotation coverage.

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?

The description is front-loaded with the core purpose, then provides usage guidelines, example, error handling, and safety. All sentences contribute information; it is well-structured but slightly verbose. Still efficient and clear.

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 complexity (6 parameters, 2 required, output schema exists), the description covers purpose, usage context, error behavior, safety, license note, and a concrete example. It is complete enough for an agent to select and invoke the tool correctly without needing additional information.

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 good parameter descriptions; the description adds value by providing a typical input example that demonstrates parameter interaction (e.g., business_hours_only effect on mode) and an output example, which helps the agent understand how parameters map to results. Slightly above baseline due to the concrete, contextual example.

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 verb 'compute' and the resource 'SLA due', distinguishes wall-clock vs business hours, and explicitly differentiates from sibling tool 'deadline_planner' by stating '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?

Explicitly says 'Use when a response or resolution clock has started and one due moment is needed' and 'Not for multi-step project schedules (deadline_planner)', providing clear when-to-use and when-not-to-use guidance with an alternative tool name.

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

A4.6/5.0
Disambiguation5/5

Every tool targets a clearly distinct temporal operation: business-day arithmetic, backward project scheduling, time-zone meeting overlap, recurrence expansion, and SLA due computation. The descriptions explicitly state what each tool is not for, making confusion unlikely.

Naming Consistency3/5

All names use underscores, but the structure varies: business_days (noun_noun), deadline_planner (noun_verb), meeting_overlap (noun_noun), recurrence_expand (noun_verb), sla_due (abbreviation+adjective). No consistent verb_noun or action_resource pattern, making prediction harder.

Tool Count5/5

With five tools, the set covers core time-ops needs—business days, deadlines, meetings, recurrences, and SLAs—without bloat. Each tool earns its place, and the count is ideal for focused servers.

Completeness4/5

The surface is well-scoped for the stated domain, covering business-day logic, planning, meeting scheduling, recurrence, and SLA timing. Minor gaps exist (e.g., no timezone conversion or general date difference) but are arguably out of scope or trivially handled externally.

Resources