AI for Coders
Answer a few questions and get your developer setup: the right AI coding tool, the exact install for your OS, and a ready-to-paste CLAUDE.md / AGENTS.md.
Question 1
Last verified:
What it does: picks your tool, then sets it up like a pro
The right tool for terminal agents isn't the one for your editor, and the install differs by OS. Answer a few questions (what you're building, where the AI works, repo size, your OS) and get:
- the tool that fits your surface and workflow
- the exact install command
- a ready-to-paste project-rules file
- context tools worth adding for a large codebase
The point isn't to crown one tool; they're all good. Some picks have a free tier or trial to learn on, others don't: Claude Code, for one, runs on a paid Claude plan. The result shows the real price for your pick and says plainly when the work outgrows it.
Four lessons most coders learn too late
- A project-rules file is the highest leverage. A short
CLAUDE.mdorAGENTS.mdat your repo root — stack, build/test commands, conventions, hard "never do this" rules. The agent reads it before every task, so it stops guessing. This tool generates a starter. - Manage the agent like a junior dev. Small scoped tasks, constraints written down, review every diff, work on a branch.
- Match the model to the job. Opus-class for hard refactors and architecture; faster GPT/Codex-class for tight agent loops; long-context Gemini-class to search a huge codebase. The frontier model by default just burns time and budget.
- Don't reach for MCP first. A plain CLI command usually beats an MCP server, and a focused context beats a giant one — feed the few files that matter, not the whole tree.
The method: maintained data, a developer's lens
Recommendations run on the same maintained data as the rest of Skuto — the matrix behind the AI chooser and the prices behind the plan picker, straight from vendor pages and re-read weekly by an automated scan. "Last verified" only moves when we re-checked. No vendor pays to appear. Once set up, the prompt fixer sharpens the instructions you hand the agent.
Honest limits: AI coding tools ship changes weekly — install paths, model names and free-tier limits drift. What's here was correct as of the date below; the tool's own docs (linked in the result) are the source of truth. Full process on our how we test page.
Frequent questions
Which AI coding tool should I use? +
There's no single best one; there's a best fit for how you work. For agentic work in the terminal, Claude Code and the OpenAI Codex CLI lead; inside an editor, Cursor and the GitHub Copilot agent are the natural picks; for a genuinely huge codebase, a long-context model like Gemini earns its place. This tool asks what you're building, where you want the AI to work and how big your repo is, then names the tool that fits and shows the exact install for your operating system.
What is a CLAUDE.md or AGENTS.md file, and do I need one? +
It's a short project-rules file the agent reads before it touches your code: the stack, the commands to build and test, the conventions to follow and the things never to do. It is the single highest-leverage thing you can set up, because it turns vague guesses into informed ones on every request. The tool generates a starter scaffold for your tool (CLAUDE.md for Claude Code, AGENTS.md for Codex and others) that you copy into your repo root and edit.
How do I match the model to the job? +
Use the heavy model only where it pays off. A complex refactor or tricky architecture call wants an Opus-class model; fast agent loops where you iterate many times lean toward a GPT or Codex-class model that is quick and cheap; a search across a very large codebase wants a long-context Gemini-class model. Most day-to-day editing does not need the frontier model at all, and reaching for it by default just burns time and budget.
Do I need MCP servers to get value? +
No, and reaching for MCP first is a common trap. Most of what people set up an MCP server for, a plain CLI command in your project-rules file does more simply and more reliably. Get the basics right first: a good CLAUDE.md / AGENTS.md, small scoped tasks and reviewing diffs. Add an MCP server only when there's a specific integration a CLI genuinely can't cover.
Is it safe to let an AI agent edit my codebase? +
Treat the agent like a capable but junior developer. Give it small, scoped tasks, write the constraints down, and review every diff before you accept it; never let it run on sensitive code or production without a human reading the change. Work on a branch, keep commits small, and you keep all the speed with none of the "what did it just do" surprises.
Tools you might need next
- Free Skuto Prompt Fixer Paste your prompt and get a better one back, with a plain explanation of why each change works.
- Free AI for Beginners Brand new to AI and not sure where to start? Answer a few simple questions and we'll point you to the one assistant that fits what you want to do: honest, with sources, no hype. Start here.
- Free Get More From AI Already using AI but feel you're scratching the surface? Answer a few questions and get a personal plan to level up: the right assistant for what you do, the plan that's actually worth it, and the settings and prompts that unlock more.