{"slug": "clai-a-lean-cli-tool-for-llm-pipelines", "title": "Clai – A Lean CLI Tool for LLM Pipelines", "summary": "Clai, a new CLI tool for LLM pipelines, lets users pipe text from stdin to an LLM and print the result to stdout, with support for named prompts, inline prompt overrides, and local models. Version 0.3.0 is available via Homebrew, and its creator Max Rodrigo is seeking feedback and contributions.", "body_md": "# Clai – A Lean CLI Tool for LLM Pipelines\n\nThe core concept is almost absurdly simple. Clai reads from stdin, sends the content to an LLM of your choice, prints the result to stdout, and exits. No REPL, no session state, no background processes. It's a pure filter in the Unix tradition — the kind of thing you compose with `|`\n\nand forget about.\n\nHere's what the daily workflow looks like in practice:\n\n```\ngit diff | clai commit\ncat article.txt | clai summarize | glow\npbpaste | clai tldr\ncurl -s example.com/article.html | clai -e \"Extract the three main concepts\"\n```\n\nThe last example is where it gets interesting — you can pass an inline prompt override with `-e`\n\ninstead of relying on a named preset. That's powerful when you need one-off transformations that don't warrant saving a prompt file.\n\nClai ships with a library of named prompts, and each one is just a file with YAML frontmatter. That means you can add your own, override the bundled ones, or organize them however makes sense for your team. I keep mine in a shared dotfiles repo so everyone on the team gets the same defaults.\n\nFor reasoning-heavy tasks, there are four strategies built in: chain-of-draft, chain-of-thought, tree-of-thought, and self-refine. I reach for chain-of-thought on anything that requires step-by-step logic, and self-refine when I want the model to critique its own output before returning it. The difference is noticeable on longer, more technical prompts.\n\nProvider support covers the major players, and I'm actively adding more. You can also point Clai at a local model — nothing leaves your machine, which matters if you're working with sensitive codebases or just want zero latency on a personal machine. The local model path was one of the design decisions I'm most proud of; too many CLI LLM tools lock you into a specific provider and make self-hosting an afterthought.\n\nInstallation is a single Homebrew command:\n\n```\nbrew install maxrodrigo/tap/clai\n```\n\nThis is v0.3.0 — a few weeks old and rough around the edges. I'm genuinely looking for feedback on what's missing. If you find yourself piping text through LLMs regularly and wish there were a lighter tool for it, I'd love to hear whether Clai fits the gap or where it falls short. Contributions are very welcome at this stage.\n\n[Next Galaxy Z Fold8 vs Reality: Ultra-Wide Fold Tested →](/en/news/5093/)", "url": "https://wpnews.pro/news/clai-a-lean-cli-tool-for-llm-pipelines", "canonical_source": "https://promptcube3.com/en/news/5096/", "published_at": "2026-08-05 10:46:05+00:00", "updated_at": "2026-08-05 10:54:19.331662+00:00", "lang": "en", "topics": ["developer-tools", "ai-tools", "large-language-models"], "entities": ["Clai", "Max Rodrigo", "Homebrew"], "alternates": {"html": "https://wpnews.pro/news/clai-a-lean-cli-tool-for-llm-pipelines", "markdown": "https://wpnews.pro/news/clai-a-lean-cli-tool-for-llm-pipelines.md", "text": "https://wpnews.pro/news/clai-a-lean-cli-tool-for-llm-pipelines.txt", "jsonld": "https://wpnews.pro/news/clai-a-lean-cli-tool-for-llm-pipelines.jsonld"}}