Business days, meeting overlap and recurrence expansion, deterministic. 3 of 5 tools free.
Do business-day math that skips weekends and your holiday list. FREE.
Either add N business days to start_date (set add_days), or count the business days between start_date and end_date (set end_date). Typical input {"start_date": "2026-03-02", "add_days": 10} returns {"result_date": "2026-03-16", "result_weekday": "Monday", ...}; with end_date set it returns {"business_days_between": N, "from": ..., "to": ...}.
Use when the span must exclude weekends and named holidays. Not for plain calendar-day differences, which are a direct subtraction, and not for scheduling backward from a fixed deadline (deadline_planner). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "dates must be YYYY-MM-DD"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
| Name | Required | Description | Default |
|---|---|---|---|
| add_days | No | Business days to add; negative subtracts. Range -5000 to 5000. Ignored when end_date is provided. | |
| end_date | No | Optional end date, ISO YYYY-MM-DD. When set, the tool counts business days between start_date and end_date instead of adding. | |
| holidays | No | Optional list of ISO YYYY-MM-DD dates to treat as non-working days, e.g. ["2026-12-25"]. | |
| start_date | Yes | Anchor date in ISO format YYYY-MM-DD, e.g. "2026-03-02". |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses crucial behavioral traits beyond the annotations: it declares that errors return a structured JSON with a fix message rather than a protocol error, and states that the tool is read-only and idempotent (consistent with annotations). It also explains the two mode-switching logic via parameters. This adds significant value beyond the annotations.
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?
The description is front-loaded with the core purpose, includes example inputs/outputs, usage guidance, error behavior, and safety note—all in a compact, well-structured form. Every sentence serves a purpose without redundancy.
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?
Given the tool's moderate complexity (dual modes, holiday list, error handling, output schema present), the description covers all essential aspects: purpose, mode selection, error handling, idempotency, and read-only guarantee. The output schema exists, so detailed return values are not required in the description.
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 coverage is 100%, so the baseline is 3. The description adds some value by explaining the dual-mode behavior and showing example inputs/outputs, but the parameter details (format, defaults, mutual exclusivity) are already well covered in the schema. The description does not add critical meaning beyond what the schema provides.
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 uses a specific verb-resource pair ('Do business-day math') and immediately distinguishes the tool's dual modes (adding days vs. counting between dates). It clearly states what the tool does and how it differs from simple calendar operations.
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 description explicitly tells when to use ('when the span must exclude weekends and named holidays') and when not to ('not for plain calendar-day differences' and 'not for scheduling backward from a fixed deadline'), and names the alternative tool 'deadline_planner'. This is exemplary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Plan a task schedule backward from a hard deadline in business days. PREMIUM (license).
Given ordered tasks with business-day durations, returns each task's start/end dates, the latest safe start, and slack from today. Typical input {"due_date": "2026-06-01", "tasks": [{"name": "Draft", "days": 3}, {"name": "Review", "days": 2}]} returns {"schedule": [...], "latest_safe_start": "YYYY-MM-DD", "slack_business_days_from_today": N, "verdict": "..."}.
Use when the end date is fixed and steps must be placed backward from it. Not for forward counting from a start date (business_days) and not for response-time targets (sla_due). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "due_date must be YYYY-MM-DD"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
| Name | Required | Description | Default |
|---|---|---|---|
| tasks | Yes | Ordered list of task objects, each {"name": str, "days": int} where days is the business-day duration (1-365); the first 30 tasks are scheduled. | |
| due_date | Yes | The deadline, ISO YYYY-MM-DD. | |
| holidays | No | Optional list of ISO YYYY-MM-DD dates treated as non-working days. | |
| buffer_days | No | Business days of safety margin kept free before due_date, clamped to 0-365. Default 1. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds significant behavioral context beyond these: it documents that the tool never raises protocol errors on invalid input (returns an error object instead), describes the licensing restriction ('PREMIUM'), limits task scheduling to the first 30 tasks, and confirms idempotency explicitly. None of these details are present in the annotations, and there is no contradiction with the annotated hints.
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?
The description is well-organized and front-loaded with the core purpose and the critical licensing note. It then covers input/output example, usage guidance, error behavior, and safety. Every sentence serves a distinct purpose (scope, example, usage rules, error handling, idempotency). No redundant content is present. It could be slightly more concise (e.g., the error section is a bit long), but overall it is efficient and structured.
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?
Given the tool's moderate complexity (4 parameters, output schema), the description covers all necessary aspects: the fundamental backward-scheduling logic, input/output structure (including an example), usage rules vs siblings, error response format (ensuring the agent knows how to interpret failures), idempotency and safety for retries, licensing restrictions, and the task limit. The presence of an output schema is noted, but the description still explains the returned fields meaningfully. Nothing critical is missing.
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 100%, so the baseline is 3. The description adds value by providing a concrete example of the tasks array structure and the expected output fields, which helps an agent understand parameter interplay. It also clarifies behavioral limits (first 30 tasks scheduled) and the purpose of buffer_days as a safety margin, which reinforces the schema. This extra context lifts the score above the baseline but does not reach a 5, as the schema already documents each parameter thoroughly.
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 precise verb-resource pair: 'plan a task schedule backward from a hard deadline in business days.' It immediately clarifies scope (backward scheduling from a fixed end date) and distinguishes itself from sibling tools by explicitly stating 'Not for forward counting from a start date (business_days) and not for response-time targets (sla_due).' The example input/output reinforces the tool's specific functionality, making it unmistakably distinct from related tools.
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 description provides clear usage context: 'Use when the end date is fixed and steps must be placed backward from it. Not for forward counting from a start date (business_days) and not for response-time targets (sla_due).' It names the specific sibling alternatives and gives explicit when-to/when-not-to instructions. Additionally, it explains error handling behavior ('never raises a protocol error — it returns {"error": ...}') and retry safety ('it is always safe to retry'), which are actionable guidelines for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find the shared meeting window across time zones inside working hours. FREE.
Give one UTC offset per participant and an optional working-hours window. Typical input {"offsets_utc": [-8, 1, 5.5]} returns {"overlap_utc": ["HH:MM", "HH:MM"], "overlap_minutes": N, "local_windows": [...]}; when no shared window exists it returns {"overlap": null, "verdict": "..."}.
Use when people in different zones need one shared slot. Not for converting a single known time between zones, and not for expanding a recurring series (recurrence_expand). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "times must be HH:MM"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
| Name | Required | Description | Default |
|---|---|---|---|
| work_end | No | Working day end, 24h HH:MM; must be later than work_start. Default "17:00". | 17:00 |
| work_start | No | Working day start, 24h HH:MM local in every zone. Default "09:00". | 09:00 |
| offsets_utc | Yes | One UTC offset per participant, each between -14 and +14; fractional offsets allowed, e.g. [-8, 1, 5.5]. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations (which already mark readOnly and idempotent) by detailing error behavior ('never raises a protocol error — returns an error object'), retry safety, and output structure when no overlap exists. This adds significant behavioral context annotations alone lack.
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?
Every sentence earns its place. The description opens with purpose, gives an example, then states usage boundaries, error handling, and idempotency. It is compact yet comprehensive, with no filler except the minor 'FREE.' which does not detract.
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?
Given the presence of an output schema (not shown but indicated as true), the description covers purpose, parameters, example I/O, error behavior, usage guidelines, and sibling differentiation. It fully equips an AI agent 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.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100% (baseline 3). The description adds value by providing a typical input example, explaining that offsets_utc represents one offset per participant, and that work_start/work_end form an optional working-hours window. This ties the schema to real usage without contradicting it.
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?
First sentence clearly states the tool finds the shared meeting window across time zones within working hours. It explicitly distinguishes from siblings like recurrence_expand by stating 'not for expanding a recurring series' and differentiates from time zone conversion.
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?
Provides explicit when-to-use ('Use when people in different zones need one shared slot') and when-not-to-use ('Not for converting a single known time... Not for expanding a recurring series'). Names an alternative tool (recurrence_expand) and explains error handling behavior for safe retries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Expand a recurrence rule into a concrete list of ISO dates. FREE.
Set every_days for a fixed interval, or weekly_on for specific weekdays. Typical input {"start_date": "2026-01-05", "every_days": 14, "count": 3} returns {"dates": ["2026-01-05", "2026-01-19", "2026-02-02"]}.
Use when a recurrence rule has to become concrete dates. Not for counting working days in a span (business_days) and not for finding a slot across zones (meeting_overlap). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "start_date must be YYYY-MM-DD"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | How many dates to generate; values outside 1-60 are clamped into that range. Default 10. | |
| weekly_on | No | Weekday names to recur on, e.g. ["mon", "thu"]; full names like "monday" also work. | |
| every_days | No | Interval in days between occurrences; use this OR weekly_on, not both. | |
| start_date | Yes | First date of the series, ISO YYYY-MM-DD. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description reinforces these and adds critical behavioral detail: the tool never raises a protocol error on invalid input, instead returning a structured error object with fix instructions. This is valuable beyond annotations.
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?
Every sentence earns its place: purpose, example, usage guidance, error behavior, safety note. The description is front-loaded with the core action and is no longer than needed. Ideal structure.
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?
Given the richness of annotations, input schema, and presence of an output schema, the description covers all necessary aspects: input format, example, usage scope, error handling, and safety guarantees. No gaps remain.
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 coverage is 100%, so baseline is 3. The description adds value by providing a typical input example, clarifying the mutual exclusivity of 'every_days' and 'weekly_on', and explaining the error format. This helps the agent understand parameter relationships and output structure.
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 starts with a clear verb+resource: 'Expand a recurrence rule into a concrete list of ISO dates.' It provides an example and distinguishes from siblings like 'business_days' and 'meeting_overlap', making the tool's exact purpose unmistakable.
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?
Explicitly states when to use ('when a recurrence rule has to become concrete dates') and when not to use, naming two sibling tools as alternatives. This gives clear, actionable guidance for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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.
| 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. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
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.
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.
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.
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.
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.
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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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Business-day, SLA, cron and recurrence calculations — offline, holiday-aware, no network.
Deterministic date arithmetic with auditable receipts: business days, due dates, holidays.
Deterministic time tools for AI agents: timezone conversion, business-day math, cron interpretation.
Time zone conversion, meeting-slot finding across countries, DST checks and .ics invites. All.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
