Claude Code Skills Setup for Vibe Coding (Zero to Hero)

Claude Code works well out of the box, but the default setup has no process, no memory of your conventions and no opinion about how much code to write. Skills fix that. A skill is a folder with a SKILL.md file that Claude loads when it is relevant, so you stop pasting the same instructions into chat. This guide shows how to combine four things into one setup: Superpowers (a development process), Ponytail (a bias toward less code), OmniRoute (a model-routing gateway, with an important warning) and your own Agent Skills.

By the end you will have a verified install path for each, a workflow that uses them at the right stage, a worked SaaS-dashboard example, and a clear idea of which ones to skip. Last verified: 7 October 2026, against each tool's official repository and Anthropic's documentation.

#Quick answer: the starter stack

If you only read one section: install Superpowers first, add Ponytail once you notice Claude over-building, write two or three project skills for your own conventions, and treat OmniRoute as optional and use-with-care.

text/plugin install superpowers@claude-plugins-official
/plugin marketplace add DietrichGebert/ponytail
/plugin install ponytail@ponytail

Labels used below: FACT is from official docs or a repository, RECOMMENDATION is our opinion, COMMUNITY is what developers report.

#What is vibe coding?

Vibe coding is building software by describing what you want to an AI and steering the result, rather than writing the code yourself. Andrej Karpathy coined the term in a 2 February 2025 post on X, describing it as a way of working where you "fully give in to the vibes" and "forget that the code even exists".

That original meaning is the careless end of the spectrum: accept what the AI writes, paste errors back, repeat. It is fine for a throwaway prototype. For anything you will maintain, charge for or put real data into, you want the other end: AI writes, you set the process and review the output. The tools in this article exist to make that second mode practical.

#Why vanilla Claude Code is only the beginning

Out of the box, Claude Code will happily start coding the moment you describe a feature. Four problems follow from that:

1. No process. It does not brainstorm, plan or test first unless you ask every time.
2. Over-building. Agents tend to add libraries, wrappers and options you did not request.
3. Repeated instructions. Your conventions live in your head or in an ever-growing CLAUDE.md.
4. One model for everything. Simple and hard tasks cost the same unless you intervene.

Skills, plugins and a gateway each address one of these. The official docs describe the difference between CLAUDE.md and skills clearly: CLAUDE.md loads every turn, while a skill's body loads only when used, so large reference material costs little until it is needed (FACT, Claude Code docs).

#The Claude Code skill stack at a glance

#1. Superpowers: a development process for your agent

Superpowers is a free, MIT-licensed set of skills that makes the agent follow a structured software process instead of jumping straight to code. It is maintained by Jesse Vincent (obra) and Prime Radiant, and it now ships in Anthropic's official plugin marketplace.

#The problem it solves

Without a process, the agent codes before the requirements are clear, skips tests and declares things "done" without checking. Superpowers adds the stages a careful engineer would follow.

#The workflow it enforces (FACT, from the README)

1. brainstorming: asks questions, explores alternatives and presents a design for you to approve.
2. using-git-worktrees: creates an isolated branch workspace with a clean test baseline.
3. writing-plans: breaks work into small tasks with exact file paths and verification steps.
4. subagent-driven-development: dispatches a fresh subagent per task with review between tasks, or runs inline.
5. test-driven-development: RED-GREEN-REFACTOR; code written before a test is deleted.
6. requesting-code-review: reviews against the plan by severity; critical issues block progress.
7. finishing-a-development-branch: verifies tests, then offers merge, PR, keep or discard.

It also includes systematic debugging and receiving-code-review skills.

#Install

text/plugin install superpowers@claude-plugins-official

Alternative via the maintainer's marketplace:

text/plugin marketplace add obra/superpowers-marketplace
/plugin install superpowers@superpowers-marketplace

Start a new session after installing. Skills trigger automatically when relevant, and you can also name one directly.

#Try it

textI want to add CSV export to the reports page. Let's brainstorm this first.

Expect questions about format, size limits and permissions before any code. Approve the design, then ask it to write the plan.

#Limits and when not to use it

• The README's own caveat: the framework relies on the agent following the skill triggers; an agent that ignores them can drift from the plan or repeat work.
• Overhead. For a one-line fix or a typo, a brainstorm-plan-review loop is slower than just doing it. Say "skip the process, just fix this" for trivial work.
• Token use. Subagents and reviews cost more tokens than a single pass. That is the trade you make for reliability.

#2. Ponytail: make the agent write less code

Ponytail is a skill that tells the agent to act like a lazy senior developer: do the simplest thing that works before writing anything new. It was created by Dietrich Gebert and is MIT-licensed. Its core is a ladder the agent climbs before coding: does this need to exist at all, is it already in the codebase, does the standard library cover it, does a native platform feature, does an installed dependency, can it be one line, and only then write the minimum code.

#Install (FACT, from the README)

text/plugin marketplace add DietrichGebert/ponytail
/plugin install ponytail@ponytail

#Commands

#Example

Ask for "a date picker for the booking form". A default agent may add a picker library, a wrapper component and a stylesheet. With Ponytail active, the ladder points to the native <input type="date"> first. You can reproduce that comparison in your own repo in two minutes, which is a better test than any chart.

#What the evidence actually says

The README reports roughly 54% less code, about 20% cheaper and about 27% faster on 12 tasks in a FastAPI and React codebase with Haiku 4.5 (n=4). Those are the author's own numbers.

An independent write-up from Scott Logic (Colin Eberhardt) is worth reading before you rely on them. It found the core skill is about 100 lines of markdown restating the YAGNI principle, and that the original benchmark's baseline was unfair. With a simple prompt, "Follow YAGNI principles, and one-liner solutions", the author reached 6.9 lines of code on average versus 8.25 for Ponytail on small tasks. Hacker News commenters also questioned the size of the repository around a short prompt (COMMUNITY).

Our read (RECOMMENDATION): Ponytail is a convenient, packaged version of an idea you could write in a line. Its extras, like the review and audit commands and the debt ledger, are the reason to install it rather than paste a sentence into CLAUDE.md. Treat the percentage claims as unproven for your codebase.

#When not to use it

• Exploratory spikes where you want options laid out.
• When you need extensibility now, such as a public library API. Minimal code can mean less flexibility; Ponytail itself says input validation, security and accessibility basics are never to be skipped.
• Alongside heavy TDD, where you may prefer lite so it does not fight the test-first steps.

#3. OmniRoute: a model-routing gateway (read the warning first)

OmniRoute is an open-source, MIT-licensed AI gateway that exposes one local endpoint and routes requests across many providers, with fallback when one is rate-limited or down. Its README describes a four-tier fallback (subscription, API key, cheap, free), a local dashboard and support for tools including Claude Code, Codex, Cursor and Cline.

#Install and connect (FACT, from the README and a setup guide)

bashnpm install -g omniroute
omniroute                      # dashboard at http://localhost:20128

Or with Docker:

bashdocker run -p 20128:20128 diegosouzapw/omniroute

Then connect a provider in the dashboard and wire up Claude Code:

bashomniroute setup-claude
omniroute launch --profile auto-coding-free

These set ANTHROPIC_BASE_URL to the local endpoint. The OpenAI-style endpoint is http://localhost:20128/v1.

#The warning you need before using it

Anthropic's gateway documentation says it does not endorse, maintain or audit third-party gateway products, and does not support routing Claude Code to non-Claude models through any gateway (source). OmniRoute's headline use, sending Claude Code traffic to free or non-Claude models, falls outside what Anthropic supports. It may work; if it breaks, that is your problem to debug.

Three more things to know:

1. Privacy. The setup guide itself warns that requests route through third-party free providers and advises against sending sensitive or production code that way.
2. Billing. Per Anthropic's docs, when a gateway credential is active, traffic is billed per token to the owner of that credential and the subscription limits do not apply. Setting only ANTHROPIC_BASE_URL keeps a saved claude.ai login as the active credential.
3. Volatile free tiers. OmniRoute states that free provider terms, quotas and models change without notice. Its token-saving figures (15 to 95%) are the project's own claims and depend on your workload.

#Best use and when to skip it

• Good fit: personal side projects and experiments where code is not sensitive and you want fallback or cost control (RECOMMENDATION).
• Skip it: client code, regulated data, or any team setup where you need support from Anthropic. If a team needs a gateway, use Anthropic's supported approach, which means a gateway that exposes a supported Anthropic-format API (docs).
• Skip it if you are new. It adds a moving part before you have learned the basics.

#4. Agent Skills: build your own

An Agent Skill is a folder containing a SKILL.md file: YAML frontmatter that says when to use it, and Markdown that says how. Claude Code skills follow the open Agent Skills standard, so some work across other tools, and Claude Code adds its own fields.

#Where they live (FACT, docs)

#Example 1: a project convention skill

markdown---
name: api-conventions
description: Our REST API conventions. Use when adding or changing API routes.
---

- Collections at `/resource`, items at `/resource/:id`.
- Return `{ "error": { "code", "message" } }` for failures.
- Validate input at the route boundary; never trust the client.

#Example 2: a deploy skill you must trigger yourself

markdown---
name: deploy
description: Deploy the app to production
disable-model-invocation: true
allowed-tools: Bash(git *) Bash(npm *)
---

1. Run the test suite. Stop if anything fails.
2. Build, then deploy using `npm run deploy`.
3. Report the deployed version.

disable-model-invocation: true means only you can run it by typing /deploy. The docs recommend this for anything with side effects.

#Rules that matter

• Write a precise description. Claude uses it to decide when to load the skill.
• Keep SKILL.md under 500 lines; move reference material into supporting files.
• Each line is a recurring cost once loaded, so state what to do rather than narrating why.
• Move procedures out of CLAUDE.md. The docs suggest this when a section grows from a fact into a multi-step procedure.
• Pre-approve tools narrowly with allowed-tools.

#How these tools work together

Do not think of four separate tools. Think of one pipeline, with each tool covering a stage.

textIdea
 ↓   Superpowers: brainstorming (questions → approved design)
Plan
 ↓   Superpowers: writing-plans + git worktree
Context
 ↓   Your skills: api-conventions, testing rules, deploy
Code
 ↓   Ponytail: smallest solution; Superpowers: TDD + subagents
Routing (optional)
 ↓   OmniRoute or direct API: cheaper model for simple tasks
Test
 ↓   Superpowers: verification before completion
Review
 ↓   Superpowers: code review; Ponytail: /ponytail-review
Refactor
 ↓   Ponytail: /ponytail-audit, /ponytail-debt
Deploy
     Your /deploy skill (manual trigger only)

RECOMMENDATION: the one real tension is Ponytail (do less) versus Superpowers (plan, test, review thoroughly). They address different things, process versus size of solution, but if you see Claude skipping tests to save lines, drop Ponytail to lite.

#Build your first "super Claude Code" setup

1. Update Claude Code and open a project you can afford to experiment in.
2. Install Superpowers (/plugin install superpowers@claude-plugins-official) and start a new session.
3. Test it with a small feature request; confirm it asks questions before coding.
4. Add Ponytail with the two marketplace commands. Run /ponytail-help to confirm it loaded.
5. Create one project skill from the api-conventions example above, adapted to your stack.
6. Create a manual /deploy skill with disable-model-invocation: true.
7. Skip OmniRoute until you have used the first four for a week.
8. Review what loaded. Use /plugin to see what is enabled and disable anything you do not use.

#Real project example: a SaaS dashboard

Goal: a dashboard with authentication, PostgreSQL, API routes, tests and deployment. The prompts below are starting points, not guaranteed outputs.

Planning.

textBuild a SaaS dashboard: email login, a Postgres `projects` table, CRUD API
routes, and a list page. Let's brainstorm before any code.

Superpowers asks about auth method, tenancy, and what "done" means. You approve a design, then it writes a task plan in a worktree.

Implementation. Each plan task goes to a subagent with tests first. With Ponytail active, expect a plain SQL migration and the framework's built-in auth before any extra dependency.

Debugging.

textThe projects list returns 500 for new users. Use systematic debugging.

You get a reproduce, hypothesize, test loop instead of random edits.

Testing. Ask for verification before it says "done": "Run the tests and show me the output before you claim this works."

Review.

textRequest a code review against the plan, then run /ponytail-review on the diff.

Ship. Type /deploy. Because the skill is manual-only, it will not run on its own.

#Before vs after

We are not claiming measured percentages. Cost and speed depend on your project; measure them on two or three real tasks before you decide.

#Common mistakes

• Installing everything at once. Conflicting instructions confuse the agent. Add one tool, use it, then add the next.
• Too many subagents for small tasks, which burns tokens.
• Vague skill descriptions, so skills never trigger or trigger constantly.
• Huge skills. Past 500 lines, split into supporting files.
• Accepting code you did not read. Process reduces mistakes; it does not remove them.
• Skipping security. Review auth, input handling and secrets yourself.
• Routing sensitive code through free providers.
• Unnecessary routing before you have a cost problem.
• Stale skills. Check them when your stack or the tool updates.
• Overengineering the setup itself when a three-line CLAUDE.md would do.

#Security considerations

• A skill is code you are asking an agent to obey. Read third-party skills before installing, especially ones with allowed-tools or hooks.
• Hooks run commands. Plugins can ship hooks; review them.
• Scope tool permissions narrowly, as in Bash(git *), not blanket shell access.
• Never commit secrets, including OmniRoute's auto-generated .env.
• Do not send private code to providers you have not vetted.

#Advanced tips

• Use context: fork to run a skill in an isolated subagent so research does not fill your main context.
• Use paths in frontmatter to limit when a skill auto-activates.
• Use dynamic context injection, for example !`git diff HEAD`, to give a skill live data before Claude sees it.
• Set model or effort per skill so cheap tasks use a lighter setting.
• Use /ponytail-debt regularly so deliberate shortcuts are tracked rather than forgotten.
• Commit project skills so your team gets the same behavior.

#Troubleshooting

#Which skills should you install first?

• Beginner: Superpowers only, plus one project skill. Learn the workflow before adding more.
• Intermediate: add Ponytail, a manual /deploy skill and a testing-rules skill.
• Advanced or agentic: add forked-context skills, per-skill model settings and, if you accept the trade-offs, a gateway like OmniRoute on non-sensitive projects.

#Final recommended stack

1. Superpowers for process.
2. Ponytail for restraint, at lite if it clashes with TDD.
3. Two to five custom skills that encode your conventions.
4. A manual-only deploy skill.
5. OmniRoute only for non-sensitive experiments, knowing Anthropic does not support non-Claude routing.

Then run one real feature through it and compare to your old way. If it is not better for you, remove what does not help.

#Want this built into your team's workflow?

Setting up skills is the easy part; the hard part is deciding what your team's agents should and should not be allowed to do. If you want an AI-assisted development workflow or a production agent built with proper guardrails, get a scope estimate for your AI agent, or read about our AI agent development service. For related background, see building AI agents with tool calling, reliable AI agents in production, AI guardrails and safety and LLM cost optimization.

#FAQ

#What are Claude Code skills?

Skills are folders with a SKILL.md file that give Claude reusable instructions. Claude loads one when its description matches the task, or you run it directly with /skill-name. The body loads only when used, unlike CLAUDE.md.

#How do I add skills to Claude Code?

Create .claude/skills/<name>/SKILL.md in a project or ~/.claude/skills/<name>/SKILL.md for all projects. To add someone else's, install a plugin with /plugin marketplace add <owner/repo> then /plugin install <name>@<marketplace>.

#What is the difference between skills, plugins and MCP servers?

Skills are instruction files. Plugins bundle skills with hooks, commands and configuration so they can be shared. MCP servers are live connections to external tools and data. They solve different problems and work together.

#Is Superpowers worth installing?

For anything beyond tiny edits, yes: it adds brainstorming, planning, test-driven development and review. It costs extra tokens and time, so turn it off for trivial changes.

#Does Ponytail really cut code by 54%?

That is the author's own benchmark figure. An independent analysis by Scott Logic found a simple YAGNI prompt matched it on small tasks. Test it on your own codebase before trusting the number.

#Is OmniRoute safe to use with Claude Code?

It can work, but Anthropic does not endorse third-party gateways or support routing Claude Code to non-Claude models. Free providers also see your prompts, so avoid sensitive or production code.

#Can I use these tools with Cursor or Codex?

Superpowers lists support for more than a dozen agents including Codex, Cursor, Gemini CLI and GitHub Copilot CLI. Ponytail and Agent Skills also target several tools. Check each README for the current install steps.

#Can skills slow Claude Code down?

Yes, if you load too many or write large ones. Every loaded line stays in context. Keep skills short and disable ones you do not use.

#Sources

• Claude Code docs: Skills
• Claude Code docs: LLM gateways
• Agent Skills open standard
• Superpowers by obra (GitHub)
• Ponytail by Dietrich Gebert (GitHub)
• OmniRoute (GitHub)
• Scott Logic: ponytail, YAGNI and the problem with prompt benchmarks
• DeployU: OmniRoute setup guide