ai-dev-tools
Skill0 starsChanged 3 months agoMITView on GitHub
Installs AI coding agent CLIs on macOS - asks which of Claude Code, Codex, Gemini, Copilot, Grok Build, Kimi Code, then uses official installers, subscription sign-ins, and permission guardrails. Use for "install claude code", "set up codex/gemini/copilot/pi CLI", "AI coding agents on my Mac". Not for using the agents, prompt authoring, MCP servers, API integration, or local LLMs.
- Installs packages
In this repository21 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- add-skillSkill
- publish-repoSkill
- cloud-dev-setupSkill
- dev-cli-toolsSkill
- docker-on-macSkill
- dotfiles-setupSkill
- editor-setupSkill
- git-ssh-identitySkill
- homebrew-setupSkill
- language-runtimesSkill
- mac-dev-appsSkill
- mac-maintenanceSkill
- macos-defaultsSkill
- macos-dev-setupSkill
- macos-security-baselineSkill
- macos-system-prepSkill
- mobile-dev-setupSkill
- web-dev-setupSkill
- zsh-setupSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 29
After install, state the threat model in one paragraph: agents execute commands and edit files.
- Very specific: line 36
Ask which to install. First inventory duplicates (which -a claude codex gemini copilot grok kimi 2>/dev/null — an existing install means …
- Distinctive: line 95
All agents: keep secrets out of repos the agent works in.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
AI Dev Tools
Installs the agentic coding CLIs — a day-one install class of its own by 2026 — via each vendor's current official channel (most now ship native installers; some are brew/npm), authenticated with subscriptions the user already has. Also the right moment to set security guardrails: these tools get read/write + exec on a machine that holds SSH keys and cloud sessions.
When NOT to use
- Using/configuring agents beyond install (prompts, CLAUDE.md/AGENTS.md content, MCP servers) → project work
- Anthropic/OpenAI API integration in code → SDK docs, not setup
- Local models (Ollama, LM Studio) → different category; mention only
- Editors with AI (Cursor) →
editor-setup
Safety rails
- Auth is browser sign-in with existing subscriptions — never ask for, echo, or store API keys during setup.
- Install only the CLIs the user selects.
- After install, state the threat model in one paragraph: agents execute commands and edit files; recommend per-project permission allowlists, reviewing dangerous-command prompts, and container/worktree sandboxes for sensitive repos. Don't silently maximize permissions.
Workflow
Ask which to install. First inventory duplicates (which -a claude codex
gemini copilot grok kimi 2>/dev/null — an existing install means update
that channel, not add a second). npm routes need Node ≥ 22
(→ language-runtimes). Then per selection (verified commands, sources
and fallbacks: references/ai-cli-matrix.md):
# Claude Code (Anthropic) - native installer is primary; brew cask/npm secondary.
# Fetch first and let the user see it: never pipe a remote script straight into a
# shell on someone's machine, even from a vendor you trust.
curl -fsSL https://claude.ai/install.sh -o /tmp/claude-install.sh
less /tmp/claude-install.sh && sh /tmp/claude-install.sh
claude --version && claude doctor # then `claude` -> browser login (Pro/Max/Team or Console)
# Codex CLI (OpenAI) - same two-step; or npm i -g @openai/codex / brew install --cask codex
curl -fsSL https://chatgpt.com/codex/install.sh -o /tmp/codex-install.sh
less /tmp/codex-install.sh && sh /tmp/codex-install.sh
codex --version # first run -> "Sign in with ChatGPT" (Plus/Pro/Business)
# Gemini CLI (Google)
brew install gemini-cli # or: npm i -g @google/gemini-cli
gemini --version # Google-account OAuth; generous free tier
# Copilot CLI (GitHub) - the STANDALONE cli; `gh copilot` extension is deprecated/archived
npm install -g @github/copilot # or: brew install --cask copilot-cli
copilot # /login with the Copilot-subscribed account
# Grok Build (xAI) - official since 2026-05
curl -fsSL https://x.ai/cli/install.sh -o /tmp/grok-install.sh # SuperGrok / X Premium+
less /tmp/grok-install.sh && sh /tmp/grok-install.sh
# Kimi Code (Moonshot) - successor of kimi-cli (auto-migrates config)
curl -fsSL https://code.kimi.com/kimi-code/install.sh -o /tmp/kimi-install.sh
less /tmp/kimi-install.sh && sh /tmp/kimi-install.sh
kimi # /login: subscription OAuth (preferred; a pay-as-you-go
# API-key mode exists - enter it inside the tool's own
# login flow only, never via chat or shell args)
# pi (Earendil / Mario Zechner) - minimal open-source agent, multi-provider
npm install -g --ignore-scripts @earendil-works/pi-coding-agent # preferred; the vendor
# also ships an install.sh at https://pi.dev/install.sh
pi # /login: ChatGPT, Claude, Copilot, xAI, OpenRouter
# subscription OAuth, or provider API keys via envInstall-channel policy: prefer brew/npm where a real package exists (Gemini, Copilot, Codex, Claude Code casks) — reviewable and update-managed. Where only a shell installer exists, fetch it to a file, read it, then run it — the two-step above. These are the vendors' documented installers (verified against vendor docs; sources in the reference), but an agent piping any remote script straight into a shell is the exact pattern registry scanners flag, so this skill never does it. A cautious user can, read it, then run it — offer that.
Guardrails (after install)
- Claude Code: permission rules live in
.claude/settings.json(project) /~/.claude/settings.json— start from deny-by-prompt defaults; don't pre-approve broad Bash. - All agents: keep secrets out of repos the agent works in. Git worktrees isolate changes (nice for review), not credentials or processes — real isolation for sensitive repos means a container/VM or separate user account without the host's keys, cloud sessions, or docker socket. Review each tool's data/telemetry settings on first run.
- Updates: Claude Code self-updates (native install); npm installs update via npm; brew casks via brew. One channel per tool — mixing npm + native installs leaves two binaries fighting on PATH.
Instruction-file conventions (when asked)
AGENTS.md is the emerging cross-tool standard: native in Codex, Grok
Build, OpenCode, Amp; Gemini reads it via the context.fileName setting;
Claude Code reads CLAUDE.md and imports with @AGENTS.md. Config homes:
~/.claude + ~/.claude.json, ~/.codex/config.toml, ~/.gemini/,
~/.copilot/.
Verify
Each selected CLI: --version prints; auth status confirmed (claude
doctor, codex /status, gh auth status unrelated — Copilot CLI has
/login state); one trivial prompt answered in a scratch directory.
Output spec
Done means: selected CLIs installed from one channel each, signed in via subscription browser flows, versions reported, guardrail paragraph delivered, and no API keys touched. Note in the summary that this tool class churns monthly — re-verify install commands against the reference/vendor docs when they fail.
Gotchas
gh copilot(the gh extension) is deprecated and archived — the standalonecopilotCLI replaced it; old guides mislead.- Claude Code via npm needs Node 22+; the native installer needs no Node at all — prefer it on fresh machines.
- Brew's
claude-codecask lags the native channel ~a week and doesn't auto-update by default. - Two installs of the same agent (npm + native) = stale-version confusion;
which -a claudeexposes it. - Grok/Kimi package names are inconsistently mirrored by third parties — use the official install scripts, not lookalike npm packages (supply-chain risk).
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

