ci-optimize
Optimize GitHub Actions workflow wait time with measured evidence. Use for "speed up CI", "why is GitHub Actions slow", workflow comparisons, or /ci-optimize. Route local command timing to /build-optimize.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/paulnsorensen/git-gouda --skill ci-optimize- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ci-optimize automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
CI optimization
Measure GitHub Actions wait time before changing. Preserve required checks, artifacts, and failure behavior.
Discipline
Iron Law: Capture the baseline before proposing a concrete edit.
Explicit authorization is required before destructive cleanup, paid infrastructure, dependency installation, source edits, or remote dispatch.
Red Flags — stop when you notice these:
- A check, artifact, workload, or failure path is removed to create a speed result.
- A rerun, partial job page, or changed validation contract enters the primary cohort.
- A local result or zero exit status replaces a CI comparison.
| Rationalization | Why it fails | Required action |
|---|---|---|
| "The cache change is obvious, so I can apply it now." | Measurement does not approve mutation. | Present the plan and wait. |
| "Parallel jobs add their durations." | The metric ends at the latest selected completion. | Measure from run creation. |
| "The rerun uses the same workflow, so it is comparable." | Schema version 1 excludes reruns from primary wait. | Keep reruns as diagnostics. |
Workflow
- Read repository instructions. Identify authoritative verification commands.
- Select one workflow, event class, workload, validation contract, and selected job set.
- Read references/github.md before capturing runs. Read references/schemas.md before constructing inputs.
- Capture baseline initial attempts and every selected attempt-specific jobs page.
- Capture the planned sample count plus headroom for exclusions. Normalize the baseline.
- Inspect eligible and excluded observations.
- For a mixed request, read references/local.md before defining local timing. Define a local run plan. Name the exact command, warmup and sample counts, cache operations, isolation, output paths, and cost.
- For a mixed request, obtain explicit approval for the local run plan.
- Present one concrete edit plan.
- Name affected files, expected benefit, risks, verification, and any established rollback.
- Obtain explicit edit-plan approval before any tracked-source edit, dispatch, or remote mutation.
- Apply the approved change through existing implementation and verification workflows.
- Repeat the complete CI capture with the same boundary. Include queue and startup delay.
- Normalize the after dataset. Compare datasets with an explicit minimum sample count.
- Read comparison JSON. Require
comparability: true. - Verify required checks, coverage, artifacts, and failure behavior.
- Report observations without promising a numeric gain. Stop after the report or when required input is missing.
Skip only local timing for a CI-only request. Local timing cannot establish CI wait improvement. Keep cache cohorts separate.
Acknowledgements record approved environment, cache-state, or local-command differences. They cannot waive workload, validation, identity, or equivalent-coverage mismatches. They do not prove causation or authorize edits.
Commands
Resolve CI_OPTIMIZE_HELPER from the actual loaded SKILL.md directory.
Resolve symlinks before using scripts/ci_optimize.py.
Never derive the helper path from the consumer repository's current directory.
The helper does not execute commands, edit workflows, install dependencies, dispatch runs, or commit changes.
Run commands from the consumer repository's working directory:
python3 "$CI_OPTIMIZE_HELPER" ci --input BEFORE-CAPTURES.json --output BEFORE.json
python3 "$CI_OPTIMIZE_HELPER" ci --input AFTER-CAPTURES.json --output AFTER.json
python3 "$CI_OPTIMIZE_HELPER" compare --before BEFORE.json --after AFTER.json --minimum-samples N --output COMPARISON.json
Run this sequence separately for approved cache cohorts with distinct output paths.
Use --force only to replace an existing explicit output file.
Run python3 "$CI_OPTIMIZE_HELPER" --self-test to check that excluded runs do not change the job set.
Evidence and report
The CI metric spans run creation to the latest selected job completion. Use initial attempts only for the primary cohort. Do not sum parallel job durations. Report status, workflow and selected-job boundary, eligible and excluded counts, medians and range, and delta. Report checks, artifacts, limitations, next approval, and evidence paths. Preserve excluded observations and their reasons. Return no more than 200 words. Do not rename unrelated gates, add auto-fix checks, or change local build behavior.
FAQ
What does the ci-optimize skill do?
Optimize GitHub Actions workflow wait time with measured evidence. Use for "speed up CI", "why is GitHub Actions slow", workflow comparisons, or /ci-optimize. Route local command timing to /build-optimize.
How do I install ci-optimize?
Run npx skills add https://github.com/paulnsorensen/git-gouda --skill ci-optimize in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ci-optimize/ (personal) or .claude/skills/ci-optimize/ (project).
Which AI agents can use ci-optimize?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ci-optimize safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ci-optimize?
It is published by paulnsorensen in paulnsorensen/git-gouda. It has 53 recorded installs.
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