How do I install the Spark Recipe Calendar Audit skill?

Run npx skillmds@latest add readdle/spark-recipe-calendar-audit in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Spark Recipe Calendar Audit safe to use?

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Which AI agents work with Spark Recipe Calendar Audit?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Spark Recipe Calendar Audit free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Spark Recipe Calendar Audit?

readdle (@readdle) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Spark Recipe Calendar Audit by readdle

Name: Spark Recipe Calendar Audit
Rating: 4.666666666666667 (3 reviews)
Author: readdle

File contents

Recipe: Calendar Audit

Analyze meeting load over a week or custom time range. Count meetings, estimate total hours, identify the busiest days, flag back-to-back chains, and surface free blocks.

Prerequisite: Read the use-spark base skill for command reference and filter syntax.

Access level required: read-only.

Steps

Step 1: Pull events for the period

For the current week:

spark events --week

For a custom range:

spark events --start 2026-04-13 --end 2026-04-17

Record each event's date, start time, end time, and title.

Step 2: Check free time

spark availability --week

Or for the same custom range:

spark availability --start 2026-04-13 --end 2026-04-17

This shows free slots within working hours (08:00-20:00), skipping weekends and events marked "free."

Step 3: Compute metrics

From the events list, calculate:

Total meetings: count of events
Total meeting hours: sum of all event durations
Per-day breakdown: meetings and hours per day
Busiest day: the day with the most meeting hours
Lightest day: the day with the fewest meetings (best for deep work)
Back-to-back chains: sequences of 2+ meetings with no gap between them
Longest free block: the largest contiguous free window from the availability output

Step 4: Check across calendars (optional)

If the user has multiple calendars or accounts:

spark events --week --in user@work.com
spark events --week --in user@personal.com

Compare meeting loads across contexts.

Step 5: Present the audit

Report:

Summary: N meetings totaling X hours this week (Y% of working hours)
Per day: table of meetings and hours per day, flagging the busiest and lightest
Back-to-back: list any chains of consecutive meetings (flag chains of 3+)
Free blocks: the longest free windows available for deep work
Observations: any patterns worth noting (e.g., mornings packed but afternoons free, one day completely booked)

Tips

Run this on Monday to plan the week, or Friday to review how the week went.
Back-to-back chains of 3+ meetings are worth flagging - they leave no buffer for breaks or follow-ups.
The ratio of meeting hours to total working hours (assume 8-10 hours/day) gives a quick "meeting load" percentage.
For a forward-looking audit, use --start and --end with next week's dates.
Events marked "free" in the calendar don't count against availability - they won't inflate the meeting load.
Combine with recipe-schedule-meeting to find the best slots for new meetings in a busy week.
If the user has recurring meetings, patterns will be consistent week-to-week. Focus commentary on what's unusual.

--- name: spark-recipe-calendar-audit description: >- Analyze meeting load over a time range: total meetings, meeting hours, busiest days, back-to-back chains, and free blocks. metadata: version: 1.0.0 requires: skills: - use-spark accessLevel: read-only --- # Recipe: Calendar Audit Analyze meeting load over a week or custom time range. Count meetings, estimate total hours, identify the busiest days, flag back-to-back chains, and surface free blocks. **Prerequisite:** Read the `use-spark` base skill for command reference and filter syntax. **Access level required:** read-only. ## Steps ### Step 1: Pull events for the period For the current week: ```bash spark events --week ``` For a custom range: ```bash spark events --start 2026-04-13 --end 2026-04-17 ``` Record each event's date, start time, end time, and title. ### Step 2: Check free time ```bash spark availability --week ``` Or for the same custom range: ```bash spark availability --start 2026-04-13 --end 2026-04-17 ``` This shows free slots within working hours (08:00-20:00), skipping weekends and events marked "free." ### Step 3: Compute metrics From the events list, calculate: - **Total meetings:** count of events - **Total meeting hours:** sum of all event durations - **Per-day breakdown:** meetings and hours per day - **Busiest day:** the day with the most meeting hours - **Lightest day:** the day with the fewest meetings (best for deep work) - **Back-to-back chains:** sequences of 2+ meetings with no gap between them - **Longest free block:** the largest contiguous free window from the availability output ### Step 4: Check across calendars (optional) If the user has multiple calendars or accounts: ```bash spark events --week --in user@work.com spark events --week --in user@personal.com ``` Compare meeting loads across contexts. ### Step 5: Present the audit Report: - **Summary:** N meetings totaling X hours this week (Y% of working hours) - **Per day:** table of meetings and hours per day, flagging the busiest and lightest - **Back-to-back:** list any chains of consecutive meetings (flag chains of 3+) - **Free blocks:** the longest free windows available for deep work - **Observations:** any patterns worth noting (e.g., mornings packed but afternoons free, one day completely booked) ## Tips - Run this on Monday to plan the week, or Friday to review how the week went. - Back-to-back chains of 3+ meetings are worth flagging - they leave no buffer for breaks or follow-ups. - The ratio of meeting hours to total working hours (assume 8-10 hours/day) gives a quick "meeting load" percentage. - For a forward-looking audit, use `--start` and `--end` with next week's dates. - Events marked "free" in the calendar don't count against availability - they won't inflate the meeting load. - Combine with `recipe-schedule-meeting` to find the best slots for new meetings in a busy week. - If the user has recurring meetings, patterns will be consistent week-to-week. Focus commentary on what's unusual.

Frequently asked questions

Spark Recipe Calendar Audit