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Moltline RegClock

Timeline Export

timeline_export
Read-onlyIdempotent

Export computed deadlines as an iCalendar file and CSV rows. PREMIUM (license).

Typical input {"deadlines": , "incident_ref": "INC-2026-041"} returns {"ics": "BEGIN:VCALENDAR...", "csv": "regime,obligation,...", "events": 4}. Each dated deadline becomes a VEVENT with the citation in the description and an alarm alarm_hours_before it; rows without a fixed time limit are listed in the CSV only. Use when the timeline needs to land in a calendar or a ticket. Not for computing deadlines. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "deadlines must be a non-empty list of rows from compute_deadlines"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deadlinesYesrows from compute_deadlines / compute_deadlines_multi.
incident_refNoyour incident reference, prefixed to every event summary.
calendar_nameNoX-WR-CALNAME for the calendar file.Incident reporting deadlines
alarm_hours_beforeNohours before each due instant to fire a VALARM (0 disables).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses concrete behavior: each dated deadline becomes a VEVENT with citation and alarm, undated rows appear only in CSV, invalid input returns an error object rather than raising a protocol error, and retrying is safe. This is rich, accurate behavioral detail that materially helps an agent invoke and interpret 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?

The description is long but dense and well-ordered: primary purpose first, then a concrete input/output example, behavioral specifics, usage guidance, error semantics, and retry safety. Every sentence adds useful information; there is no filler or repetition of schema content.

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 tool with four parameters, an output schema, and rich annotations, this description is complete: it covers expected inputs, output format, edge cases, error behavior, idempotency, and read-only safety. An agent has everything needed to select and call 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%, so the schema already documents all four parameters. The description adds useful context beyond the schema: a typical input example, the expectation that deadlines rows come from compute_deadlines or compute_deadlines_multi, and how alarm_hours_before affects VEVENT alarms. This justifies a score above the baseline of 3.

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 opens with a specific verb and resource: 'Export computed deadlines as an iCalendar file and CSV rows.' It also distinguishes the tool from its compute-focused siblings by stating 'Not for computing deadlines,' so an agent can tell it apart from compute_deadlines and compute_deadlines_multi.

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?

It gives explicit usage context: 'Use when the timeline needs to land in a calendar or a ticket,' and an explicit exclusion: 'Not for computing deadlines.' It does not name the exact alternative tool to use for computing deadlines, but the sibling context and mention of compute_deadlines make the routing reasonably 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

A4.6/5.0
Disambiguation5/5

Each tool targets a distinct stage of the incident-reporting workflow: classify_event qualifies the incident, compute_deadlines and compute_deadlines_multi produce deadlines, deadline_status monitors them, explain_rule cites the underlying rule, and timeline_export and validate_report handle output and pre-submission checks. No two tools are plausible substitutes; the single vs. multi-regime split between the two deadline tools is explicitly described.

Naming Consistency3/5

Most action tools follow a verb_noun pattern (classify_event, compute_deadlines, explain_rule, list_regimes, validate_report), but three tools use noun_noun or reversed forms (deadline_status, holiday_calendar, timeline_export). The convention is readable but not uniform, making it a mixed pattern rather than a consistent one.

Tool Count5/5

Nine tools is a well-scoped set for a regulatory deadline engine. Each tool maps to a necessary capability—discovery, classification, computation, status, explanation, calendar data, export, and validation—without redundant or filler entries.

Completeness5/5

The surface covers the full lifecycle: discover regimes, classify an incident, compute single or multi-regime deadlines, assess their status, inspect the statutory rule, export to calendar/CSV, and validate a draft report. Holiday and regime metadata tools fill supporting gaps, leaving no obvious dead-end for the stated purpose.

Resources