commands Skill
> Comprehensive AI-powered code review for PRs and local changes — enterprise-grade alternative to CodeRabbit
Want an agent-native computer in the browser? Try HappyCapy.
Cloud sandbox for AI agents · No setup · Run autonomous workflows from your browser
Affiliate link — we may earn a commission at no extra cost to you.
Why use this skill
commands is most useful when you want an agent workflow that is more structured than an ad-hoc prompt. Instead of restating the same expectations every time, a dedicated SKILL.md file gives the assistant a repeatable brief. In this case, the core value is clarity: the repo already frames the workflow around utility skills tasks, and the skill source gives you a portable starting point you can evaluate, adapt, and reuse. The inferred platform for this skill is Claude Code Skills, which helps you judge whether it is likely to feel native in your current agent ecosystem or whether it is better treated as a general reference.
That matters because AI assistants are better when the operating context is explicit. A good skill turns hidden team expectations into visible instructions. It can name preferred tools, describe failure modes, define what “done” looks like, and reduce the amount of corrective prompting you need after the first draft. For developers exploring the wider SKILL.md ecosystem, this page helps answer the practical question: is this skill specific and maintained enough to be worth trying?
How to evaluate and use it
Start with the source repo and the preview below. The preview tells you whether the instructions are actionable or just aspirational. Strong skills usually describe triggers, recommended tools, steps, and known pitfalls. Weak skills tend to stay generic. This one lives in koreyba/EverFreeNote, which gives you a concrete repo context, update history, and direct ownership trail.
Once you confirm the scope looks right, test it on a small task before making it part of a larger workflow. If it improves consistency, keep it. If it is too broad, outdated, or conflicts with your own process, treat it as a reference rather than a drop-in rule. That is the healthiest way to use directory-discovered skills: not as magic plugins, but as reusable operational knowledge that still deserves judgment.
SKILL.md preview
Previewing the source is one of the fastest ways to judge whether a skill is truly useful. This snippet comes from the public file in the linked repository.
# Code Review > Comprehensive AI-powered code review for PRs and local changes — enterprise-grade alternative to CodeRabbit ## When to use - "code review" - "review my PR" - "review PR #123" - "check my changes" - "what's wrong with my code" - "security review" - "full review" - "/review" - "/review-pr" ## Dependencies - External: `gh` CLI (GitHub), `git` ## Modes ### 1. Local review (uncommitted changes) Reviews `git diff` — changes not yet committed. ### 2. Branch review (vs main/master) Reviews all changes in current branch compared to main. ### 3. PR review (GitHub) Fetches diff from GitHub PR and can post comments. ### 4. Focused review User can request specific focus: security, performance, bugs, style, etc. --- ## How to execute ### Step 0: Check if review needed **Skip review if:** - PR is draft (`gh pr view --json isDraft`) - PR is already closed/merged - Only documentation changes (.md, .txt, LICENSE) - Only config changes (.json, .yaml, .toml) without code impact - Trivial changes (<5 lines, whitespace only, version bumps) **Inform user and ask to confirm if they still want review.** --- ### Step 1: Determine mode Ask user or detect automatically: - If PR number provided → PR review - If uncommitted changes exist → local review - If on feature branch → branch review - If specific focus requested → apply focus filter ### Step 2: Get diff **Local:** ```bash git diff HEAD ``` **Branch (vs main):** ```bash DEFAULT_BRANCH=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@' || echo "main") git diff $DEFAULT_BRA ...