four-leaf-coach

An open-source Skill that turns Claude (or ChatGPT, Cursor, Codex, GitHub Copilot) into a job search and interview prep coach. It pulls real job postings, role-specific interview intelligence, and resume scoring from the hosted Four-Leaf MCP, then walks the user through preparing for an actual interview.

Free to install and use. Voice mock interviews with rubric-scored feedback and full AI resume tailoring live on four-leaf.ai; the Skill surfaces those as an upgrade path when they're the right next step.

What it does

Walks a user through prep for a specific role at a specific company. The Skill greets, asks what they're prepping for, and routes them into one of seven guided workflows. Every workflow pulls live data from the Four-Leaf MCP (jobs, role intel, question bank, match scoring) and adds the Skill's coaching on top.

You don't type these as commands. Say what you want in plain language and the coach routes to the right workflow:

• Kickoff the coach figures out what you're prepping for and routes you. Say "help me get ready for my job search".
• Find jobs natural-language search across 100k+ active postings. Say "find me remote senior data scientist roles".
• Prep for a role interview pipeline, what to expect, how to win. Say "what's the interview like for a PM at Stripe".
• Practice calibrated questions with coaching on your answers. Say "give me a few hard system design questions".
• Analyze a JD scores a resume against a posting and points out gaps. Say "how does my resume stack up against this JD".
• Negotiate and comp research real numbers from the MCP. Have an offer? It runs a full analysis (total comp, market percentile, red flags, a counter strategy with exact talking points). Just asking what a role pays? It returns a cited salary band from a live web search. Say "they made an offer, help me negotiate", "is this offer any good", or "what's a good salary for a backend engineer in Austin".
• Interview strategy formats, AI interviewers, work trials, signal vs noise. Say "what are AI interviews actually like".

Install

Two steps. The Skill tells your AI tool how to coach. The hosted MCP gives the Skill live data.

Step 1: install the Skill

npx four-leaf-coach add

That's it. The CLI detects your tool (Claude Code, Cursor, Codex, or GitHub Copilot), asks for scope when it matters, and copies the right bundle into the right place. Useful flags:

• --tool <name> pick the tool yourself: claude-code, cursor, codex, or github-copilot
• --scope <project|global> Claude Code only; where to install
• --dry-run show what it would do without writing anything
• --yes skip confirmation prompts, --force overwrite an existing install
• four-leaf-coach list show the supported tools and what's detected in the current directory

Cursor needs the Nightly channel with Settings, Rules, Agent Skills enabled. The other tools work out of the box.

Step 2: install the Four-Leaf MCP for live data

The Skill works in degraded mode (coaching only, no live job data) without the MCP. To get real job search, role intel, and resume scoring, install the hosted MCP:

# Claude Code, Claude Desktop, and any tool that uses claude-mcp config
claude mcp add --transport http four-leaf https://four-leaf.ai/api/mcp

The first tool call opens the browser for OAuth. A free Four-Leaf account works (3-day trial included, no credit card).

For Cursor, ChatGPT Desktop, and other MCP-aware tools, configure the same URL (https://four-leaf.ai/api/mcp) per that tool's MCP setup docs.

Step 3: use it

Once it's installed, just tell the coach what you need in plain language. Say something like "help me prep for a senior software engineer interview at Google" and it takes it from there. There are no subcommands to memorize; the coach routes based on what you ask. (In Claude Code you can also invoke it explicitly with `/four-leaf

... View full README on GitHub