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docker-expert
Expert Docker engineer specializing in containerization, multi-stage builds, and container orchestration. Masters Docker Compose, security hardening, and production-grade container deployment strategies.
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devops cicd AI Skills
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GitHub
aws-expert
AWS infrastructure expertise for the z360 application. Auto-activates when working with AWS CLI commands, infrastructure analysis, cost optimization, or security reviews.
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GitHub
managing-projects-beads
Interact with the "Beads" (bd) CLI to track issues, plan work, and manage dependencies. Use this to maintain context across sessions.
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GitHub
deploy-safety
Ensures deployments go to correct environments. Apply when deploying or pushing to production.
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GitHub
unikraft
Kraft CLI commands for building and deploying Unikraft unikernels. Use when working with Kraftfiles, deploying to Unikraft Cloud, or managing unikernel instances.
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GitHub
flow-next-worktree-kit
Manage git worktrees (create/list/switch/cleanup) and copy .env files. Use for parallel feature work, isolated review, clean workspace, or when user mentions worktrees.
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GitHub
flow-next-plan-review
Carmack-level plan review via RepoPrompt or OpenCode. Use when reviewing Flow epic specs or design docs. Triggers on /flow-next:plan-review.
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GitHub
flow-next-impl-review
John Carmack-level implementation review via RepoPrompt or OpenCode. Use when reviewing code changes, PRs, or implementations. Triggers on /flow-next:impl-review.
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GitHub
flow-next-plan-review
Carmack-level plan review via RepoPrompt or Codex. Use when reviewing Flow epic specs or design docs. Triggers on /flow-next:plan-review.
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GitHub
flow-next-impl-review
John Carmack-level implementation review via RepoPrompt or Codex. Use when reviewing code changes, PRs, or implementations. Triggers on /flow-next:impl-review.
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GitHub
commit
Reviews staged git changes and drafts a concise commit message. Use when the user wants to commit, needs a commit message, or asks to review staged changes for committing.
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GitHub
dispatching-parallel-agents
Dispatch multiple agents in parallel for independent problems. Use when (1) 3+ test files failing with different root causes, (2) multiple modules broken independently, (3) multiple components need separate fix...
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GitHub
subagent-driven-development
Orchestrate implementation through fresh subagents per task with two-stage review (spec compliance then code quality). Use when (1) executing a plan with multiple independent tasks, (2) staying in current sessi...
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GitHub
code-reviewer
Expert code review for Python, microservices, security, and production best practices. Automatically activated when code review is needed to identify bugs, security issues, and quality problems.
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GitHub
task-processor-auto
Process tasks autonomously with automated PR reviews and gap analysis after each PR creation/commit.
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GitHub
pr-review-loop
Monitor PR for code review, analyze feedback with AI, implement fixes, and merge when approved with CI green.
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GitHub
test-plan-generator
Generate comprehensive E2E test plans from PRDs, task lists, or descriptions with environment-aware prerequisites and issue tracking.
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GitHub
test-plan-generator
Generate comprehensive E2E test plans from PRDs, task lists, or descriptions with environment-aware prerequisites and issue tracking.
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GitHub
task-processor-auto
Process tasks autonomously with automated PR reviews and gap analysis after each PR creation/commit.
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GitHub
pr-review-loop
Monitor PR for code review, analyze feedback with AI, implement fixes, and merge when approved with CI green.
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GitHub
task-processor-auto
Process tasks autonomously with automated PR reviews and gap analysis after each PR creation/commit.
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GitHub
pr-review-loop
Monitor PR for code review, analyze feedback with AI, implement fixes, and merge when approved with CI green.
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GitHub
test-plan-generator
Generate comprehensive E2E test plans from PRDs, task lists, or descriptions with environment-aware prerequisites and issue tracking.
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GitHub
runbook-generator
Generate operational runbooks documenting what needs to be running locally and in production for effective system testing and deployment.
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The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.