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cron-schedule-planner

cron-schedule-planner

github.com/dboeckliCloud & DevOps02.0k installsUpdated 4w ago
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About cron-schedule-planner

A command-line skill for analyzing GitHub Actions scheduled workflows across repositories. It classifies workload intensity, converts UTC schedules to local time, and reports hourly patterns, collisions, and redistribution suggestions without editing workflows.

Key features

  1. 01Collect scheduled workflows across repositories
  2. 02Heuristically classify workload intensity
  3. 03Convert UTC times to local time
  4. 04Report hourly patterns and collisions
  5. 05Suggest schedule redistribution

Use cases

  1. 01Check schedule collisions across repositories
  2. 02Find open slots for intensive builds
  3. 03Estimate queue times from recent runs
  4. 04Adjust cron times after confirmation

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/dboeckli/ai-agent-skills --skill cron-schedule-planner

After installing, type/cron-schedule-plannerin Claude Code to confirm it loaded.

Bundled filesreferences/classification-and-timezones.mdscripts/cron-schedule-planner.sh

Details

From the project README

Cron Schedule Planner

Collects GitHub Actions on.schedule cron expressions across repositories, classifies how resource-intensive each workflow is, converts the UTC cron times to a local timezone, and produces a Markdown report with an hourly histogram, collisions and concrete redistribution suggestions.

Read-only: the script never edits workflows. Suggestions are applied only after the user confirms.

Instructions

Step 1: Decide the repository scope
  • Default: all repositories of the authenticated gh user (no local checkouts needed).
  • --owner <owner> to scan a different owner.
  • --repo <owner/repo> (repeatable) for an explicit list.
  • --local <dir> to scan local checkouts instead of the GitHub API.
Step 2: Run the script
bash scripts/cron-schedule-planner.sh

Common variants:

# Specific owner, Swiss local time, report in target/
bash scripts/cron-schedule-planner.sh --owner dboeckli --tz Europe/Zurich

# Local checkouts (no GitHub API)
bash scripts/cron-schedule-planner.sh --local ~/projects/referenzen

# A few explicit repos
bash scripts/cron-schedule-planner.sh --repo dboeckli/ai-agent-skills --repo dboeckli/camel-first
Step 3: Present the results

The script prints the hourly histogram, collisions and suggestions, and writes target/cron-schedule-overview.md. Summarise:

  • how many repos / scheduled entries were found,
  • the most crowded UTC hours (collisions),
  • which high-intensity jobs sit in crowded hours.
Step 4: Apply suggestions only after confirmation

The redistribution suggestions are heuristic (they move high-intensity jobs out of crowded hours into empty ones, keeping the minute and day fields). Present them as a diff and change workflow files only after explicit confirmation. Never edit automatically.

Options

OptionMeaning
--owner <owner>GitHub owner to scan (default: authenticated user)
--repo <owner/repo>explicit repo (repeatable); disables owner scan
--local <dir>scan local checkouts under <dir> instead of GitHub
--tz <zone>local timezone for the Local column (default Europe/Zurich)
--limit <n>max repos for the owner scan (default 200)
--out <file>Markdown report (default target/cron-schedule-overview.md)
--no-reportconsole only, no report file
--top <n>max redistribution suggestions (default 5)
--queue-statsadd observed queue time per UTC hour (via gh run list)
--runs <n>max runs per repo for queue stats (default 50)

Output

target/cron-schedule-overview.md:

  • Scheduled workflows table: repo, workflow, cron (UTC), UTC time, local time, frequency, intensity, evidence.
  • Runs per UTC hour histogram (bars).
  • Runs per frequency / weekday.
  • Collisions — UTC hours with two or more scheduled runs.
  • Observed queue time per UTC hour (with --queue-stats) — average and max wait between createdAt and startedAt across recent runs, as an empirical contention signal.
  • Redistribution suggestions — high-intensity jobs in crowded hours moved to empty ones; with --queue-stats the empty hours with the lowest observed queue are preferred.

Classification

Intensity is derived heuristically from the workflow content. See references/classification-and-timezones.md for the exact patterns and the UTC/timezone rules.

  • high — Docker Compose, Testcontainers, service containers (services:), Kind/k3s cluster, matrix builds.
  • medium — Maven/Gradle full builds, Docker image builds.
  • low — lint/format/validate and other meta workflows.

Examples

Example 1: Are my scheduled builds colliding?

User says: "Do my scheduled GitHub Actions builds collide?"

Actions:

  1. Run bash scripts/cron-schedule-planner.sh --owner <owner>
  2. Report the crowded UTC hours and the high-intensity jobs in them
  3. Point to target/cron-schedule-overview.md

Result: Collision overview across all repos with concrete evidence.

Example 2: When should the Testcontainers build run?

User says: "When should I schedule the Testcontainers build?"

Actions:

  1. Run the planner and locate the crowded hours (collisions)
  2. Recommend one of the empty hours from the suggestions
  3. Offer the concrete cron diff, apply only after confirmation

Result: A low-contention slot and a ready-to-apply cron change.

Troubleshooting

gh: not found or authentication error

The script needs an authenticated gh. Run gh auth status; if that fails, the user must authenticate. Alternatively use --local <dir> with local checkouts.

Empty report

No workflow in scope has an on.schedule entry. Check the repo scope (--owner, --repo, --local) and that the workflows actually define schedule: crons.

Times look off by one hour

Cron is always UTC. Local times are computed for the current date, so daylight-saving transitions can shift them by one hour. Re-run after a DST change or adjust manually.

--queue-stats shows little or no data

GitHub reports startedAt equal to createdAt for most runs (no recorded queue), so the signal is sparse. Increase --runs to include older runs. Treat large gaps with care: they can come from approval gates, concurrency limits or manual runs, not only runner contention.

Comments

Markdown supported