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spark-recipe-calendar-audit — Claude Code skill: how to install

Analyzes meeting load via Spark over a week or custom range. It flags back-to-back call chains, calculates total hours, and surfaces open blocks for deep work.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add readdle/spark-cli-skills --skill spark-recipe-calendar-audit -a claude-code
npx skills add readdle/spark-cli-skills --skill recipe-calendar-audit -a claude-code
Open on GitHub

What spark-recipe-calendar-audit does

This recipe audits your calendar using the Spark CLI under read-only permissions. The agent runs spark events for the current week or a custom date window, then calls spark availability to inspect open slots. Working hours default to 08:00–20:00, weekend slots are skipped, and calendar entries marked "free" do not inflate meeting totals.

The resulting summary details meeting counts, total hours, the busiest day, and the lightest day for focused work. It flags back-to-back sequences where two or more meetings run without a gap. When managing multiple accounts, the --in flag lets you evaluate workload across personal and work calendars.

You need the use-spark base skill installed beforehand. Without configured Spark CLI access, the skill cannot retrieve calendar data or compute availability.

What it helps with

  • calculate total meeting hours and workload percentage for the week
  • detect back-to-back meeting chains that lack break buffers
  • identify the lightest workday for focused deep work
  • compare meeting volume across personal and work email accounts

Example prompts for the agent

  • Run a calendar audit for this week using Spark and show my open slots.
  • Audit meeting load from 2026-04-13 to 2026-04-17 and flag consecutive calls.
  • Compare my meeting hours across [email protected] and [email protected] this week.

How to install spark-recipe-calendar-audit

1Skills CLI (Vercel)

npx skills add readdle/spark-cli-skills --skill spark-recipe-calendar-audit -a claude-code
npx skills add readdle/spark-cli-skills --skill recipe-calendar-audit -a claude-code

2Manually: put the files in place

~/.claude/skills/recipe-calendar-audit/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/recipe-calendar-audit/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about spark-recipe-calendar-audit

How do I install spark-recipe-calendar-audit in Claude Code?

Run npx skills add readdle/spark-cli-skills --skill spark-recipe-calendar-audit -a claude-code. You can also place the skill file directly into ~/.claude/skills/recipe-calendar-audit/SKILL.md.

What metrics does spark-recipe-calendar-audit calculate?

It computes total meeting count, aggregate hours, busiest and lightest days, back-to-back call sequences, and the longest contiguous block of free time.

What prerequisites does this skill require?

It requires the base skill use-spark alongside Spark CLI. The skill operates strictly with read-only access.

Source text

SKILL.md · MIT
---
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 [email protected]
spark events --week --in [email protected]
```

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.

© readdle · MIT · readdle/spark-cli-skills

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