circleci-config — Codex skill for CircleCI config
This skill reviews CircleCI configuration and suggests ways to cut pipeline waste, adjust caching, and address slow jobs. Use it when CI runs drag on or pipeline behavior is flaky.
npx skills add openai/plugins --skill config -a codexWhat circleci-config does
The skill starts by identifying the longest and least stable jobs, then proposes incremental configuration changes. It examines duplicate jobs and workflow triggers, cache keys, data shared between jobs, and parallelism. Before changes are finalized, it calls for expected metric shifts and acceptance criteria.
It can draw on guidance for caching, moving data, test execution, and workflow patterns, depending on the issue. Its output includes bottlenecks, reasons for proposed edits, and a validation and rollback plan. It favors configuration changes over application edits when the config can address the problem. Blanket retries are a bad fix for deterministic failures. Bring the .circleci/ YAML files and baseline details such as job duration, failures, or cost.
What it helps with
- identify the slowest CircleCI jobs
- remove duplicate work from workflows
- set cache keys around lockfiles
- choose how jobs share generated data
- parallelize bottlenecks and define validation criteria
Example prompts for the agent
- Review
.circleci/config.yml, identify slow jobs, and propose how to validate the changes. - Check the CircleCI cache setup and assess how its keys relate to lockfiles.
- Analyze flaky test jobs and suggest where parallelism could address a bottleneck.
How to install circleci-config
1Skills CLI (Vercel)
npx skills add openai/plugins --skill config -a codex2Manually: put the files in place
.agents/skills/config/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add openai/plugins --skill config -a claude-code2Manually: put the files in place
~/.claude/skills/config/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/config/
Manually: put the files in place
.cursor/skills/config/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install openai/plugins config2Manually: put the files in place
.github/skills/config/SKILL.mdPlatform CLI
gemini skills install https://github.com/openai/plugins --path plugins/circleci/skills/configManually: put the files in place
.devin/skills/config/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: Codex skills: how to install, where they live, how to call them
Questions about circleci-config
How do I install circleci-config in Codex?
Run npx skills add openai/plugins --skill config -a codex. The skill file is at .agents/skills/config/SKILL.md.
What does circleci-config do?
It reviews CircleCI configuration for bottlenecks and suggests changes to jobs, caching, data flow, or parallelism. It also outlines validation and rollback steps.
What should I provide for a CircleCI review?
Provide the YAML files from .circleci/, describe the pain point, and share baseline metrics such as job duration, retries, or failures.
Source text
SKILL.md · MIT
--- name: circleci-config description: Optimize CircleCI configuration for speed, reliability, and maintainability. Use when users ask to improve `.circleci/config.yml`, reduce CI runtime, tune caching/workspaces/parallelism, remove pipeline waste, or fix flaky pipeline behavior caused by configuration choices. --- # CircleCI Config ## Overview Use this skill to improve CircleCI performance and stability without changing product behavior. Focus on measured bottlenecks first, then implement the smallest safe config changes with clear validation criteria. Read `references/cache-optimization.md` when the request involves `save_cache`, `restore_cache`, `persist_to_workspace`, `attach_workspace`, cache key design, dependency caching, lockfiles, or complaints about low cache hit rates, oversized caches, or wasted persistence steps. Read `references/persisting-data.md` when the request involves choosing between caches, workspaces, and artifacts, or when data is being moved between jobs inefficiently. Read `references/test-results-and-splitting.md` when the request involves slow test jobs, parallelism, flaky test visibility, missing JUnit XML, or `circleci tests run`. Read `references/patterns.md` when the request involves approvals, branch/tag filters, schedules, deploy flow structure, or environment promotion patterns. ## Inputs To Gather - `.yaml` and `.yml` files in `.circleci/` and any reusable config fragments - Current pain points: duration, flakiness, cost, or maintainability - Baseline metrics: slowest jobs, most frequent retries/failures, queue and run times - Risk tolerance for structural changes ## Workflow 1. Build a baseline. - Identify top 1-3 longest jobs and top flaky jobs. - Capture before metrics (duration, pass rate, retries). 2. Remove pipeline waste. - Eliminate duplicate jobs/workflows. - Tighten branch/tag filters and workflow triggers. 3. Improve dependency and artifact flow. - Fix cache keys to include deterministic lockfile checks. - Use workspaces/artifacts to avoid rebuilding identical outputs. - Prefer cache scopes that are narrow, reproducible, and cheap to restore. 4. Apply safe parallelism. - Parallelize only proven bottlenecks. - Keep fan-out/fan-in readable and deterministic. 5. Validate impact. - Define expected metric changes and acceptance criteria before finalizing. ## Guardrails - Prefer configuration fixes before proposing application code changes. - Do not add blanket retries to hide deterministic failures. - Preserve deployment safety gates while optimizing build/test stages. - Keep changes incremental and easy to revert. - Prefer language-specific cache directories over broad project snapshots. - Avoid cache keys that rotate every run unless the user explicitly wants effectively write-only caches. ## Output Contract Provide: 1. Baseline bottleneck summary. 2. Proposed or applied config changes with rationale. 3. Expected runtime/reliability impact. 4. Validation plan and rollback note.
© CircleCI · MIT · openai/plugins